mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 01:04:32 +02:00
video tab redesign and optimized ltxvideo
Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
+25
-11
@@ -1,8 +1,8 @@
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# Change Log for SD.Next
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## Update for 2025-07-09
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## Update for 2025-07-10
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### Highlights for 2025-07-09
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### Highlights for 2025-07-10
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In this release we finally break with legacy with the removal of the original [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) codebase which has not been maintained for a while now
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This plus major cleanup of codebase and external dependencies resulted in ~53k LoC (*lines-of-code*) reduction and spread over [~680 files](https://github.com/vladmandic/sdnext/pull/4017)!
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@@ -11,19 +11,19 @@ We also switched project license to [Apache-2.0](https://github.com/vladmandic/s
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Feature highlights include:
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- **ModernUI** layout redesign which should make it more user friendly and easier to navigate
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- Redesigned **Video** interface with native **FramePack** support
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- Redesigned [LTXVideo](https://vladmandic.github.io/sdnext-docs/Video) interface with support for general video models plus optimized [FramePack](https://vladmandic.github.io/sdnext-docs/FramePack) and [LTXVideo](https://vladmandic.github.io/sdnext-docs/LTX) support
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- New background replacement and relightning methods using **Latent Bridge Matching** and new **PixelArt** processing filter
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- New **LLM/VLM** models available for captioning and prompt enhance
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- Compute improvements
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And (as always) many bugfixes and improvements to existing features!
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And (*as always*) many bugfixes and improvements to existing features!
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*Note*: We recommend clean install for this release due to sheer size of changes
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Although upgrades and existing installations are tested and should work fine!
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[ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867)
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### Details for 2025-07-09
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### Details for 2025-07-10
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- **License**
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- SD.Next [license](https://github.com/vladmandic/sdnext/blob/dev/LICENSE.txt) switched from **aGPL-v3.0** to **Apache-v2.0**
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@@ -35,14 +35,27 @@ Although upgrades and existing installations are tested and should work fine!
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*relighting*: automatic background replacement with reglighting so source image fits desired background
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with optional composite blending
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available in *img2img or control -> scripts*
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- Add **FLUX.1-Kontext-Dev** inpaint workflow
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- Support **FLUX.1** all-in-one safetensors
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- Support **TAESD** preview and remote VAE for **HunyuanDit**
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- Support for [Gemma 3n](https://huggingface.co/google/gemma-3n-E4B-it) E2B and E4B LLM/VLM models in **prompt enhance** and process **captioning**
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- **FramePack** support is now fully integrated instead of being a separate extension
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- add **FLUX.1-Kontext-Dev** inpaint workflow
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- support **FLUX.1** all-in-one safetensors
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- support **TAESD** preview and remote VAE for **HunyuanDit**
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- support for [Gemma 3n](https://huggingface.co/google/gemma-3n-E4B-it) E2B and E4B LLM/VLM models in **prompt enhance** and process **captioning**
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- **Video**
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- redesigned **Video** interface
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- support for **Generic** video models
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includes support for many video models without specific per-model optimizations
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included: *Hunyuan, LTX, WAN, Mochi, Latte, Allegro, Cog*
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supports quantization, offloading, frame interpolation, etc.
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- support for optimized [FramePack](https://vladmandic.github.io/sdnext-docs/FramePack)
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with *t2i, i2i, flf2v* workflows
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LoRA support, prompt enhance, etc.
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now fully integrated instead of being a separate extension
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- support for optmized [LTXVideo](https://vladmandic.github.io/sdnext-docs/LTX)
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with *t2i, i2i, v2v* workflows
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optional native upsampling and video refine workflows
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LoRA support with different conditioning types such as Canny/Depth/Pose, etc.
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- **UI**
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- major update to modernui layout
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- redesign of the Flat UI theme
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- redesign of the *Flat* UI theme
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- **WIKI**
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- new [Parameters](https://vladmandic.github.io/sdnext-docs/Parameters/) page that lists and explains all generation parameters
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- **Compute**
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@@ -68,6 +81,7 @@ Although upgrades and existing installations are tested and should work fine!
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- fix diffusers models non-unique hash
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- fix loading of manually downloaded diffuser models
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- fix api `/sdapi/v1/embeddings` endpoint
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- fix incorrect reporting of deleted and modified files
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- improve infotext param parsing
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- improve extensions ui search
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- improve model type autodetection
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@@ -10,6 +10,12 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
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- Feature: LoRA add OMI format support for SD35/FLUX.1
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- Refactor: sampler options
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- Video: API support
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- Remove: CodeFormer
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- Remove: GFPGAN
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- Video: LTX TeaCache and others
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- Video: LTX API
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- Video: LTX PromptEnhance
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- Video: LTX Condition preprocess
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### Blocked items
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@@ -40,7 +46,6 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
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#### Stable
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- [Diffusers-0.34.0](https://github.com/huggingface/diffusers/releases/tag/v0.34.0)
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- [WanAI-2.1 VACE](https://huggingface.co/Wan-AI/Wan2.1-VACE-14B)(https://github.com/huggingface/diffusers/pull/11582)
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- [LTXVideo-0.9.7](https://github.com/Lightricks/LTX-Video?tab=readme-ov-file#diffusers-integration)(https://github.com/huggingface/diffusers/pull/11516)
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- [Cosmos-Predict2-Video](https://huggingface.co/nvidia/Cosmos-Predict2-2B-Video2World)(https://github.com/huggingface/diffusers/pull/11695)
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#### Pending
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- [Magi](https://github.com/SandAI-org/MAGI-1)(https://github.com/huggingface/diffusers/pull/11713)
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Submodule extensions-builtin/sdnext-modernui updated: 9a4ff1ead2...54f844d291
+4
-4
@@ -949,10 +949,10 @@ def check_modified_files():
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files = [x for x in files if len(x) > 0 and (not x.startswith('extensions')) and (not x.startswith('wiki')) and (not x.endswith('.json')) and ('.log' not in x)]
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deleted = [x for x in files if not os.path.exists(x)]
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if len(deleted) > 0:
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log.warning(f'Deleted files: {files}')
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files = [x for x in files if os.path.exists(x) and not os.path.isdir(x)]
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if len(files) > 0:
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log.warning(f'Modified files: {files}')
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log.warning(f'Deleted files: {deleted}')
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modified = [x for x in files if os.path.exists(x) and not os.path.isdir(x)]
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if len(modified) > 0:
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log.warning(f'Modified files: {modified}')
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except Exception:
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pass
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ts('files', t_start)
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@@ -1,8 +1,9 @@
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import gradio as gr
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from modules import ui_sections, ui_common, ui_video_vlm
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from modules.video_models.video_utils import get_codecs
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from modules.framepack import framepack_load
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from modules.framepack.framepack_worker import get_latent_paddings
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from modules.framepack.framepack_wrappers import get_codecs, load_model, unload_model
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from modules.framepack.framepack_wrappers import load_model, unload_model
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from modules.framepack.framepack_wrappers import run_framepack # pylint: disable=wrong-import-order
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@@ -4,7 +4,7 @@ import rich.progress as rp
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from modules import shared, errors ,devices, sd_models, timer, memstats
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from modules.framepack import framepack_vae # pylint: disable=wrong-import-order
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from modules.framepack import framepack_hijack # pylint: disable=wrong-import-order
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from modules.framepack import framepack_video # pylint: disable=wrong-import-order
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from modules.video_models.video_save import save_video # pylint: disable=wrong-import-order
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stream = None # AsyncStream
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@@ -302,12 +302,12 @@ def worker(
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if is_last_section:
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break
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total_generated_frames = framepack_video.save_video(history_pixels, mp4_fps, mp4_codec, mp4_opt, mp4_ext, mp4_sf, mp4_video, mp4_frames, mp4_interpolate, pbar=pbar, stream=stream, metadata=metadata)
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total_generated_frames, _video_filename = save_video(history_pixels, mp4_fps, mp4_codec, mp4_opt, mp4_ext, mp4_sf, mp4_video, mp4_frames, mp4_interpolate, pbar=pbar, stream=stream, metadata=metadata)
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except AssertionError:
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shared.log.info('FramePack: interrupted')
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if shared.opts.keep_incomplete:
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framepack_video.save_video(history_pixels, mp4_fps, mp4_codec, mp4_opt, mp4_ext, mp4_sf, mp4_video, mp4_frames, mp4_interpolate=0, stream=stream, metadata=metadata)
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save_video(history_pixels, mp4_fps, mp4_codec, mp4_opt, mp4_ext, mp4_sf, mp4_video, mp4_frames, mp4_interpolate=0, stream=stream, metadata=metadata)
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except Exception as e:
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shared.log.error(f'FramePack: {e}')
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errors.display(e, 'FramePack')
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@@ -6,6 +6,7 @@ import numpy as np
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import torch
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import gradio as gr
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from modules import shared, processing, timer, paths, extra_networks, progress, ui_video_vlm
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from modules.video_models.video_utils import check_av
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from modules.framepack import framepack_install # pylint: disable=wrong-import-order
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from modules.framepack import framepack_load # pylint: disable=wrong-import-order
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from modules.framepack import framepack_worker # pylint: disable=wrong-import-order
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@@ -20,38 +21,6 @@ queue_lock = threading.Lock()
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loaded_variant = None
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def check_av():
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try:
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import av
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except Exception as e:
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shared.log.error(f'av package: {e}')
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return False
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return av
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def get_codecs():
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av = check_av()
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if av is None:
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return []
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codecs = []
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for codec in av.codecs_available:
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try:
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c = av.Codec(codec, mode='w')
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if c.type == 'video' and c.is_encoder and len(c.video_formats) > 0:
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if not any(c.name == ca.name for ca in codecs):
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codecs.append(c)
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except Exception:
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pass
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hw_codecs = [c for c in codecs if (c.capabilities & 0x40000 > 0) or (c.capabilities & 0x80000 > 0)]
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sw_codecs = [c for c in codecs if c not in hw_codecs]
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shared.log.debug(f'Video codecs: hardware={len(hw_codecs)} software={len(sw_codecs)}')
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# for c in hw_codecs:
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# shared.log.trace(f'codec={c.name} cname="{c.canonical_name}" decs="{c.long_name}" intra={c.intra_only} lossy={c.lossy} lossless={c.lossless} capabilities={c.capabilities} hw=True')
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# for c in sw_codecs:
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# shared.log.trace(f'codec={c.name} cname="{c.canonical_name}" decs="{c.long_name}" intra={c.intra_only} lossy={c.lossy} lossless={c.lossless} capabilities={c.capabilities} hw=False')
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return ['none'] + [c.name for c in hw_codecs + sw_codecs]
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def prepare_image(image, resolution):
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from modules.framepack.pipeline.utils import resize_and_center_crop
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buckets = [
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+76
-33
@@ -1,17 +1,13 @@
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"""
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- condition upload image
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- condition upload video
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- condition video get frames
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- custom sampler
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- new way of generate video
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- modernui
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- lora loader
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- teacache and others
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"""
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# import diffusers.LTXConditionPipeline
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import os
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import time
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import threading
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from modules import shared, sd_models, errors, timer, memstats, progress
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from modules import shared, errors, timer, memstats, progress, processing, sd_models, sd_samplers, extra_networks
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from modules.video_models.video_save import save_video
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from modules.video_models.video_utils import check_av
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from modules.processing_callbacks import diffusers_callback
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from modules.ltx.ltx_util import get_bucket, get_frames, load_model, load_upsample, get_conditions, get_generator, get_prompts, vae_decode
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@@ -38,26 +34,39 @@ def run_ltx(task_id,
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upsample_ratio:float,
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refine_enable:bool,
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refine_strength:float,
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condition_image_strength:float,
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condition_video_strength:float,
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condition_video_frames:int,
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condition_strength: float,
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condition_image,
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condition_files,
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condition_video,
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condition_video_frames:int,
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condition_video_skip:int,
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decode_timestep:float,
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image_cond_noise_scale:float,
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mp4_fps:int,
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mp4_interpolate:int,
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mp4_codec:str,
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mp4_ext:str,
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mp4_opt:str,
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mp4_video:bool,
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mp4_frames:bool,
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mp4_sf:bool,
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_overrides,
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):
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def abort(e, ok:bool=False):
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def abort(e, ok:bool=False, p=None):
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if ok:
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shared.log.info(e)
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else:
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shared.log.error(f'Video: cls={shared.sd_model.__class__.__name__} op=base {e}')
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errors.display(e, 'LTX')
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if p is not None:
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extra_networks.deactivate(p)
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shared.state.end()
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progress.finish_task(task_id)
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yield None, f'LTX Error: {str(e)}'
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from diffusers import LTXConditionPipeline # pylint: disable=unused-import
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check_av()
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progress.add_task_to_queue(task_id)
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with queue_lock:
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progress.start_task(task_id)
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@@ -69,16 +78,34 @@ def run_ltx(task_id,
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shared.state.begin('Video', task_id=task_id)
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shared.state.job_count = 1
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|
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p = processing.StableDiffusionProcessingVideo(
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prompt=prompt,
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negative_prompt=negative,
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styles=styles,
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width=width,
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height=height,
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frames=frames,
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steps=steps,
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sampler_index=sampler_index,
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seed=seed,
|
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)
|
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|
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conditions = get_conditions(
|
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width,
|
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height,
|
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condition_strength,
|
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condition_image,
|
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condition_image_strength,
|
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condition_files,
|
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condition_video,
|
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condition_video_strength,
|
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condition_video_frames,
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condition_video_skip,
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)
|
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prompt, negative, networks = get_prompts(prompt, negative, styles)
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shared.log.debug(f'Video: cls={shared.sd_model.__class__.__name__} op=init prompt="{prompt}" negative="{negative}" styles={styles} networks={networks}')
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sampler_name = processing.get_sampler_name(sampler_index)
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sd_samplers.create_sampler(sampler_name, shared.sd_model)
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shared.log.debug(f'Video: cls={shared.sd_model.__class__.__name__} op=init prompt="{prompt}" negative="{negative}" styles={styles} networks={networks} sampler={shared.sd_model.scheduler.__class__.__name__}')
|
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extra_networks.activate(p, networks)
|
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|
||||
t0 = time.time()
|
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shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
|
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@@ -95,17 +122,17 @@ def run_ltx(task_id,
|
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"callback_on_step_end": diffusers_callback,
|
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"output_type": "latent",
|
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}
|
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shared.log.debug(f'Video: cls={shared.sd_model.__class__.__name__} op=base {base_args}')
|
||||
if len(conditions) > 0:
|
||||
base_args["conditions"] = conditions
|
||||
shared.log.debug(f'Video: cls={shared.sd_model.__class__.__name__} op=base {base_args}')
|
||||
yield None, 'LTX: Generate in progress...'
|
||||
try:
|
||||
latents = shared.sd_model(**base_args).frames[0]
|
||||
except AssertionError as e:
|
||||
yield from abort(e, ok=True)
|
||||
yield from abort(e, ok=True, p=p)
|
||||
return
|
||||
except Exception as e:
|
||||
yield from abort(e, ok=False)
|
||||
yield from abort(e, ok=False, p=p)
|
||||
return
|
||||
t2 = time.time()
|
||||
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
|
||||
@@ -117,7 +144,7 @@ def run_ltx(task_id,
|
||||
if upsample_enable:
|
||||
t4 = time.time()
|
||||
shared.state.begin('Upsample')
|
||||
global upsample_pipe # python-lint: disable=global-statement
|
||||
global upsample_pipe # pylint: disable=global-statement
|
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upsample_pipe = load_upsample(upsample_pipe, upsample_repo_id)
|
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upsample_pipe = sd_models.apply_balanced_offload(upsample_pipe)
|
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upscale_args = {
|
||||
@@ -133,10 +160,10 @@ def run_ltx(task_id,
|
||||
try:
|
||||
upsampled_latents = upsample_pipe(latents=latents, **upscale_args).frames[0]
|
||||
except AssertionError as e:
|
||||
yield from abort(e, ok=True)
|
||||
yield from abort(e, ok=True, p=p)
|
||||
return
|
||||
except Exception as e:
|
||||
yield from abort(e, ok=False)
|
||||
yield from abort(e, ok=False, p=p)
|
||||
return
|
||||
latents = upsampled_latents
|
||||
t5 = time.time()
|
||||
@@ -163,19 +190,19 @@ def run_ltx(task_id,
|
||||
"callback_on_step_end": diffusers_callback,
|
||||
"output_type": "latent",
|
||||
}
|
||||
if len(conditions) > 0:
|
||||
refine_args["conditions"] = conditions
|
||||
if latents.ndim == 4:
|
||||
latents = latents.unsqueeze(0) # add batch dimension
|
||||
shared.log.debug(f'Video: cls={shared.sd_model.__class__.__name__} op=refine latents={latents.shape} {refine_args}')
|
||||
if len(conditions) > 0:
|
||||
refine_args["conditions"] = conditions
|
||||
yield None, 'LTX: Refine in progress...'
|
||||
try:
|
||||
refined_latents = shared.sd_model(latents=latents, **refine_args).frames[0]
|
||||
except AssertionError as e:
|
||||
yield from abort(e, ok=True)
|
||||
yield from abort(e, ok=True, p=p)
|
||||
return
|
||||
except Exception as e:
|
||||
yield from abort(e, ok=False)
|
||||
yield from abort(e, ok=False, p=p)
|
||||
return
|
||||
latents = refined_latents
|
||||
t8 = time.time()
|
||||
@@ -185,29 +212,45 @@ def run_ltx(task_id,
|
||||
timer.process.add('offload', t9 - t8)
|
||||
shared.state.end()
|
||||
|
||||
extra_networks.deactivate(p)
|
||||
|
||||
yield None, 'LTX: VAE decode in progress...'
|
||||
try:
|
||||
frames = vae_decode(latents, decode_timestep, seed)
|
||||
except AssertionError as e:
|
||||
yield from abort(e, ok=True)
|
||||
yield from abort(e, ok=True, p=p)
|
||||
return
|
||||
except Exception as e:
|
||||
yield from abort(e, ok=False)
|
||||
yield from abort(e, ok=False, p=p)
|
||||
return
|
||||
t10 = time.time()
|
||||
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
|
||||
t11 = time.time()
|
||||
timer.process.add('offload', t11 - t10)
|
||||
shared.state.end()
|
||||
progress.finish_task(task_id)
|
||||
|
||||
num_frames, video_file = save_video(
|
||||
pixels=frames,
|
||||
mp4_fps=mp4_fps,
|
||||
mp4_codec=mp4_codec,
|
||||
mp4_opt=mp4_opt,
|
||||
mp4_ext=mp4_ext,
|
||||
mp4_sf=mp4_sf,
|
||||
mp4_video=mp4_video,
|
||||
mp4_frames=mp4_frames,
|
||||
mp4_interpolate=mp4_interpolate,
|
||||
metadata={},
|
||||
)
|
||||
|
||||
t_end = time.time()
|
||||
num_frames = len(frames)
|
||||
resolution = f'{frames[0].width}x{frames[0].height}' if num_frames > 0 else None
|
||||
_n, _c, _t, h, w = frames.shape
|
||||
resolution = f'{w}x{h}' if num_frames > 0 else None
|
||||
summary = timer.process.summary(min_time=0.25, total=False).replace('=', ' ')
|
||||
memory = shared.mem_mon.summary()
|
||||
fps = f'{num_frames/(t_end-t0):.2f}'
|
||||
its = f'{(steps)/(t_end-t0):.2f}'
|
||||
|
||||
shared.log.info(f'Processed: frames={num_frames} fps={fps} its={its} resolution={resolution} time={t_end-t0:.2f} timers={timer.process.dct()} memory={memstats.memory_stats()}')
|
||||
yield frames, f'LTX: Generation completed | Frames {len(frames)} | Resolution {resolution} | f/s {fps} | it/s {its} '+ f"<div class='performance'><p>{summary} {memory}</p></div>"
|
||||
shared.state.end()
|
||||
progress.finish_task(task_id)
|
||||
|
||||
shared.log.info(f'Processed: fn="{video_file}" frames={num_frames} fps={fps} its={its} resolution={resolution} time={t_end-t0:.2f} timers={timer.process.dct()} memory={memstats.memory_stats()}')
|
||||
yield video_file, f'LTX: Generation completed | File {video_file} | Frames {len(frames)} | Resolution {resolution} | f/s {fps} | it/s {its} '+ f"<div class='performance'><p>{summary} {memory}</p></div>"
|
||||
|
||||
+34
-15
@@ -1,7 +1,8 @@
|
||||
import os
|
||||
import gradio as gr
|
||||
from modules import shared, ui_sections, ui_symbols
|
||||
from modules import shared, ui_sections, ui_symbols, ui_common
|
||||
from modules.ui_components import ToolButton
|
||||
from modules.video_models.video_utils import get_codecs
|
||||
from modules.ltx import ltx_process
|
||||
|
||||
|
||||
@@ -15,26 +16,44 @@ def create_ui(prompt, negative, styles, overrides):
|
||||
generate = gr.Button('Generate', elem_id="ltx_generate_btn", variant='primary', visible=False)
|
||||
with gr.Accordion(open=True, label="Size", elem_id='ltx_generate_accordion'):
|
||||
with gr.Row():
|
||||
width, height = ui_sections.create_resolution_inputs('ltx', default_width=704, default_height=512)
|
||||
width, height = ui_sections.create_resolution_inputs('ltx', default_width=832, default_height=480)
|
||||
with gr.Row():
|
||||
frames = gr.Slider(label='Frames', minimum=1, maximum=513, step=1, value=17, elem_id="ltx_frames")
|
||||
seed = gr.Number(label='Initial seed', value=-1, elem_id="ltx_seed", container=True)
|
||||
random_seed = ToolButton(ui_symbols.random, elem_id="ltx_random_seed")
|
||||
with gr.Accordion(open=False, label="Condition", elem_id='ltx_condition_accordion'):
|
||||
condition_strength = gr.Slider(label='Condition strength', minimum=0.1, maximum=1.0, step=0.05, value=0.8, elem_id="ltx_condition_image_strength")
|
||||
with gr.Tabs():
|
||||
with gr.Tab('Image', id='ltx_condition_image_tab'):
|
||||
condition_image_strength = gr.Slider(label='Condition strength', minimum=0.1, maximum=1.0, step=0.05, value=0.8, elem_id="ltx_condition_image_strength")
|
||||
condition_image = gr.Image(label='Image', type='filepath', elem_id="ltx_condition_image", visible=False)
|
||||
condition_image = gr.Image(sources='upload', type="pil", label="Image", width=256, height=256, interactive=True, tool="editor", image_mode='RGB', elem_id="ltx_condition_image")
|
||||
with gr.Tab('Video', id='ltx_condition_video_tab'):
|
||||
condition_video_strength = gr.Slider(label='Condition strength', minimum=0.1, maximum=1.0, step=0.05, value=0.8, elem_id="ltx_condition_video_strength")
|
||||
condition_video_frames = gr.Slider(label='Condition frames', minimum=1, maximum=1024, step=1, value=15, elem_id="ltx_condition_video_frames")
|
||||
condition_video = gr.Video(label='Video', type='filepath', elem_id="ltx_condition_video", visible=False)
|
||||
condition_video = gr.Video(label='Video', type='filepath', elem_id="ltx_condition_video", width=256, height=256, source='upload')
|
||||
with gr.Row():
|
||||
condition_video_frames = gr.Slider(label='Frames number', minimum=-1, maximum=1024, step=1, value=-1, elem_id="ltx_condition_video_frames")
|
||||
condition_video_skip = gr.Slider(label='Frames skip', minimum=0, maximum=1024, step=1, value=0, elem_id="ltx_condition_video_sip")
|
||||
with gr.Tab('Gallery', id='ltx_condition_batch_tab'):
|
||||
condition_files = gr.Files(label="Image Batch", interactive=True, elem_id="ltx_condition_batch")
|
||||
with gr.Accordion(open=False, label="Upsample", elem_id='ltx_upsample_accordion'):
|
||||
upsample_enable = gr.Checkbox(label='Enable upsampling', value=False, elem_id="ltx_upsample_enable")
|
||||
upsample_ratio = gr.Slider(label='Upsample ratio', minimum=1.0, maximum=4.0, step=0.1, value=2.0, elem_id="ltx_upsample_ratio", interactive=False)
|
||||
with gr.Row():
|
||||
upsample_enable = gr.Checkbox(label='Enable upsampling', value=False, elem_id="ltx_upsample_enable")
|
||||
upsample_ratio = gr.Slider(label='Upsample ratio', minimum=1.0, maximum=4.0, step=0.1, value=2.0, elem_id="ltx_upsample_ratio", interactive=False)
|
||||
with gr.Accordion(open=False, label="Refine", elem_id='ltx_refine_accordion'):
|
||||
refine_enable = gr.Checkbox(label='Enable refinement', value=False, elem_id="ltx_refine_enable")
|
||||
refine_strength = gr.Slider(label='Refine strength', minimum=0.1, maximum=1.0, step=0.05, value=0.4, elem_id="ltx_refine_strength")
|
||||
with gr.Row():
|
||||
refine_enable = gr.Checkbox(label='Enable refinement', value=False, elem_id="ltx_refine_enable")
|
||||
refine_strength = gr.Slider(label='Refine strength', minimum=0.1, maximum=1.0, step=0.05, value=0.4, elem_id="ltx_refine_strength")
|
||||
with gr.Accordion(label="Video", open=False):
|
||||
with gr.Row():
|
||||
mp4_fps = gr.Slider(label="FPS", minimum=1, maximum=60, value=24, step=1)
|
||||
mp4_interpolate = gr.Slider(label="Interpolation", minimum=0, maximum=10, value=0, step=1)
|
||||
with gr.Row():
|
||||
mp4_codec = gr.Dropdown(label="Codec", choices=['none', 'libx264'], value='libx264', type='value')
|
||||
ui_common.create_refresh_button(mp4_codec, get_codecs)
|
||||
mp4_ext = gr.Textbox(label="Format", value='mp4', elem_id="framepack_mp4_ext")
|
||||
mp4_opt = gr.Textbox(label="Options", value='crf:16', elem_id="framepack_mp4_ext")
|
||||
with gr.Row():
|
||||
mp4_video = gr.Checkbox(label='Save Video', value=True, elem_id="framepack_mp4_video")
|
||||
mp4_frames = gr.Checkbox(label='Save Frames', value=False, elem_id="framepack_mp4_frames")
|
||||
mp4_sf = gr.Checkbox(label='Save SafeTensors', value=False, elem_id="framepack_mp4_sf")
|
||||
with gr.Accordion(open=False, label="Advanced", elem_id='ltx_parameters_accordion'):
|
||||
steps, sampler_index = ui_sections.create_sampler_and_steps_selection(None, "ltx", default_steps=50)
|
||||
with gr.Row():
|
||||
@@ -43,8 +62,8 @@ def create_ui(prompt, negative, styles, overrides):
|
||||
|
||||
with gr.Column(elem_id='ltx-output-column', scale=2) as _column_output:
|
||||
with gr.Row():
|
||||
# video = gr.Video(label="Output", show_label=False, elem_id='ltx_output_video', elem_classes=['control-image'], height=512, autoplay=False)
|
||||
video = gr.Gallery(value=[], label="Output", show_label=False, elem_id='ltx_output_video', elem_classes=['control-image'], height=512)
|
||||
video = gr.Video(label="Output", show_label=False, elem_id='ltx_output_video', elem_classes=['control-image'], height=512, autoplay=False)
|
||||
# video = gr.Gallery(value=[], label="Output", show_label=False, elem_id='ltx_output_video', elem_classes=['control-image'], height=512)
|
||||
with gr.Row():
|
||||
text = gr.HTML('', elem_id='ltx_generation_info', show_label=False)
|
||||
|
||||
@@ -59,9 +78,9 @@ def create_ui(prompt, negative, styles, overrides):
|
||||
steps, sampler_index, seed,
|
||||
upsample_enable, upsample_ratio,
|
||||
refine_enable, refine_strength,
|
||||
condition_image_strength, condition_video_strength, condition_video_frames,
|
||||
condition_image, condition_video,
|
||||
condition_strength, condition_image, condition_files, condition_video, condition_video_frames, condition_video_skip,
|
||||
decode_timestep, image_cond_noise_scale,
|
||||
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf,
|
||||
overrides,
|
||||
]
|
||||
video_outputs = [
|
||||
|
||||
+39
-10
@@ -1,5 +1,6 @@
|
||||
import time
|
||||
import torch
|
||||
from PIL import Image
|
||||
from modules import devices, shared, sd_models, timer, extra_networks
|
||||
|
||||
|
||||
@@ -42,17 +43,43 @@ def load_upsample(upsample_pipe, upsample_repo_id):
|
||||
return upsample_pipe
|
||||
|
||||
|
||||
def get_conditions(condition_image, condition_image_strength, condition_video, condition_video_strength, condition_video_frames):
|
||||
def get_video_frames(fn: str):
|
||||
pass
|
||||
|
||||
def get_conditions(width, height, condition_strength, condition_image, condition_files, condition_video, condition_video_frames, condition_video_skip):
|
||||
from diffusers.pipelines.ltx.pipeline_ltx_condition import LTXVideoCondition
|
||||
conditions = []
|
||||
if condition_image is not None:
|
||||
conditions.append(LTXVideoCondition(image=condition_image, strength=condition_image_strength))
|
||||
try:
|
||||
if isinstance(condition_image, str):
|
||||
from modules.api.api import decode_base64_to_image
|
||||
condition_image = decode_base64_to_image(condition_image)
|
||||
condition_image = condition_image.convert('RGB').resize((width, height), resample=Image.Resampling.LANCZOS)
|
||||
conditions.append(LTXVideoCondition(image=condition_image, frame_index=0, strength=condition_strength))
|
||||
shared.log.debug(f'Video condition: image={condition_image.size} strength={condition_strength}')
|
||||
except Exception as e:
|
||||
shared.log.error(f'LTX condition image: {e}')
|
||||
if condition_files is not None:
|
||||
condition_images = []
|
||||
for fn in condition_files:
|
||||
try:
|
||||
if hasattr(fn, 'name'):
|
||||
condition_image = Image.open(fn.name).convert('RGB').resize((width, height), resample=Image.Resampling.LANCZOS)
|
||||
else:
|
||||
condition_image = fn.convert('RGB').resize((width, height), resample=Image.Resampling.LANCZOS)
|
||||
condition_images.append(condition_image)
|
||||
except Exception as e:
|
||||
shared.log.error(f'LTX condition files: {e}')
|
||||
if len(condition_images) > 0:
|
||||
conditions.append(LTXVideoCondition(video=condition_images, frame_index=0, strength=condition_strength))
|
||||
shared.log.debug(f'Video condition: files={len(condition_images)} size={condition_images[0].size} strength={condition_strength}')
|
||||
if condition_video is not None:
|
||||
condition_frames = get_video_frames(condition_video, num_frames=condition_video_frames)
|
||||
conditions.append(LTXVideoCondition(video=condition_frames, frame_index=0, strength=condition_video_strength))
|
||||
from modules.video_models.video_utils import get_video_frames
|
||||
try:
|
||||
condition_frames = get_video_frames(condition_video, num_frames=condition_video_frames, skip_frames=condition_video_skip)
|
||||
condition_frames = [f.convert('RGB').resize((width, height), resample=Image.Resampling.LANCZOS) for f in condition_frames]
|
||||
if len(condition_frames) > 0:
|
||||
conditions.append(LTXVideoCondition(video=condition_frames, frame_index=0, strength=condition_strength))
|
||||
shared.log.debug(f'Video condition: frames={len(condition_frames)} size={condition_frames[0].size} strength={condition_strength}')
|
||||
except Exception as e:
|
||||
shared.log.error(f'LTX condition video: {e}')
|
||||
return conditions
|
||||
|
||||
|
||||
@@ -91,9 +118,11 @@ def vae_decode(latents, decode_timestep, seed):
|
||||
timestep = torch.tensor([decode_timestep], device=devices.device, dtype=latents.dtype)
|
||||
noise_scale = torch.tensor([decode_timestep], device=devices.device, dtype=devices.dtype)[:, None, None, None, None]
|
||||
latents = (1 - noise_scale) * latents + noise_scale * noise
|
||||
frames = shared.sd_model.vae.decode(latents, timestep, return_dict=False)[0]
|
||||
frames = shared.sd_model.video_processor.postprocess_video(frames, output_type='pil')
|
||||
frames = shared.sd_model.vae.decode(latents, timestep, return_dict=False)[0] # n, c, f, h, w
|
||||
# frames = frames.squeeze(0) if frames.ndim == 5 else frames
|
||||
# frames = frames.permute(1, 2, 3, 0)
|
||||
# frames = shared.sd_model.video_processor.postprocess_video(frames, output_type='pil')
|
||||
shared.state.end()
|
||||
t1 = time.time()
|
||||
timer.process.add('vae', t1 - t0)
|
||||
return frames[0]
|
||||
return frames
|
||||
|
||||
@@ -7,12 +7,18 @@ import einops
|
||||
from modules import shared, errors ,timer, rife
|
||||
|
||||
|
||||
def get_video_filename(frames:int, codec:str):
|
||||
timestamp = datetime.datetime.now().strftime('%Y%m%d-%H%M%S')
|
||||
output_filename = os.path.join(shared.opts.outdir_video, f'{timestamp}-{codec}-f{frames}')
|
||||
return output_filename
|
||||
|
||||
|
||||
def atomic_save_video(filename, tensor:torch.Tensor, fps:float=24, codec:str='libx264', pix_fmt:str='yuv420p', options:str='', metadata:dict={}, pbar=None):
|
||||
try:
|
||||
import av
|
||||
av.logging.set_level(av.logging.ERROR) # pylint: disable=c-extension-no-member
|
||||
except Exception as e:
|
||||
shared.log.error(f'FramePack video: {e}')
|
||||
shared.log.error(f'Video: {e}')
|
||||
return
|
||||
|
||||
frames, height, width, _channels = tensor.shape
|
||||
@@ -27,7 +33,7 @@ def atomic_save_video(filename, tensor:torch.Tensor, fps:float=24, codec:str='li
|
||||
else:
|
||||
continue
|
||||
options[key.strip()] = value.strip()
|
||||
shared.log.info(f'FramePack video: file="{filename}" codec={codec} frames={frames} width={width} height={height} fps={rate} options={options}')
|
||||
shared.log.info(f'Video: file="{filename}" codec={codec} frames={frames} width={width} height={height} fps={rate} options={options}')
|
||||
video_array = torch.as_tensor(tensor, dtype=torch.uint8).numpy(force=True)
|
||||
task = pbar.add_task('encoding', total=frames) if pbar is not None else None
|
||||
if task is not None:
|
||||
@@ -64,13 +70,14 @@ def save_video(
|
||||
metadata:dict={}, # metadata for video
|
||||
pbar=None, # progress bar for video
|
||||
):
|
||||
output_video = None
|
||||
if pixels is None:
|
||||
return 0
|
||||
return 0, output_video
|
||||
t_save = time.time()
|
||||
n, _c, t, h, w = pixels.shape
|
||||
size = pixels.element_size() * pixels.numel()
|
||||
shared.log.debug(f'FramePack video: video={mp4_video} export={mp4_frames} safetensors={mp4_sf} interpolate={mp4_interpolate}')
|
||||
shared.log.debug(f'FramePack video: encode={t} raw={size} latent={pixels.shape} fps={mp4_fps} codec={mp4_codec} ext={mp4_ext} options="{mp4_opt}"')
|
||||
shared.log.debug(f'Video: video={mp4_video} export={mp4_frames} safetensors={mp4_sf} interpolate={mp4_interpolate}')
|
||||
shared.log.debug(f'Video: encode={t} raw={size} latent={pixels.shape} fps={mp4_fps} codec={mp4_codec} ext={mp4_ext} options="{mp4_opt}"')
|
||||
try:
|
||||
if stream is not None:
|
||||
stream.output_queue.push(('progress', (None, 'Saving video...')))
|
||||
@@ -86,18 +93,17 @@ def save_video(
|
||||
x = einops.rearrange(x, '(m n) c t h w -> t (m h) (n w) c', n=n)
|
||||
x = x.contiguous()
|
||||
|
||||
timestamp = datetime.datetime.now().strftime('%Y%m%d-%H%M%S')
|
||||
output_filename = os.path.join(shared.opts.outdir_video, f'{timestamp}-{mp4_codec}-f{t}')
|
||||
output_filename = get_video_filename(t, mp4_codec)
|
||||
|
||||
if mp4_sf:
|
||||
fn = f'{output_filename}.safetensors'
|
||||
shared.log.info(f'FramePack export: file="{fn}" type=savetensors shape={x.shape}')
|
||||
shared.log.info(f'Video export: file="{fn}" type=savetensors shape={x.shape}')
|
||||
from safetensors.torch import save_file
|
||||
shared.state.outputs(fn)
|
||||
save_file({ 'frames': x }, fn, metadata={'format': 'video', 'frames': str(t), 'width': str(w), 'height': str(h), 'fps': str(mp4_fps), 'codec': mp4_codec, 'options': mp4_opt, 'ext': mp4_ext, 'interpolate': str(mp4_interpolate)})
|
||||
|
||||
if mp4_frames:
|
||||
shared.log.info(f'FramePack frames: files="{output_filename}-00000.jpg" frames={t} width={w} height={h}')
|
||||
shared.log.info(f'Video frames: files="{output_filename}-00000.jpg" frames={t} width={w} height={h}')
|
||||
for i in range(t):
|
||||
image = cv2.cvtColor(x[i].numpy(), cv2.COLOR_RGB2BGR)
|
||||
fn = f'{output_filename}-{i:05d}.jpg'
|
||||
@@ -105,17 +111,17 @@ def save_video(
|
||||
cv2.imwrite(fn, image)
|
||||
|
||||
if mp4_video and (mp4_codec != 'none'):
|
||||
fn = f'{output_filename}.{mp4_ext}'
|
||||
atomic_save_video(fn, tensor=x, fps=mp4_fps, codec=mp4_codec, options=mp4_opt, metadata=metadata, pbar=pbar)
|
||||
output_video = f'{output_filename}.{mp4_ext}'
|
||||
atomic_save_video(output_video, tensor=x, fps=mp4_fps, codec=mp4_codec, options=mp4_opt, metadata=metadata, pbar=pbar)
|
||||
if stream is not None:
|
||||
stream.output_queue.push(('progress', (None, f'Video {os.path.basename(fn)} | Codec {mp4_codec} | Size {w}x{h}x{t} | FPS {mp4_fps}')))
|
||||
stream.output_queue.push(('file', fn))
|
||||
stream.output_queue.push(('progress', (None, f'Video {os.path.basename(output_video)} | Codec {mp4_codec} | Size {w}x{h}x{t} | FPS {mp4_fps}')))
|
||||
stream.output_queue.push(('file', output_video))
|
||||
else:
|
||||
if stream is not None:
|
||||
stream.output_queue.push(('progress', (None, '')))
|
||||
|
||||
except Exception as e:
|
||||
shared.log.error(f'FramePack video: raw={size} {e}')
|
||||
errors.display(e, 'FramePack video')
|
||||
shared.log.error(f'Video save: raw={size} {e}')
|
||||
errors.display(e, 'video')
|
||||
timer.process.add('save', time.time()-t_save)
|
||||
return t
|
||||
return t, output_video
|
||||
@@ -90,12 +90,12 @@ def create_ui(prompt, negative, styles, overrides):
|
||||
with gr.Row():
|
||||
width, height = ui_sections.create_resolution_inputs('video', default_width=832, default_height=480)
|
||||
with gr.Row():
|
||||
frames = gr.Slider(label='Frames', minimum=1, maximum=1024, step=1, value=15, elem_id="video_frames")
|
||||
frames = gr.Slider(label='Frames', minimum=1, maximum=1024, step=1, value=17, elem_id="video_frames")
|
||||
seed = gr.Number(label='Initial seed', value=-1, elem_id="video_seed", container=True)
|
||||
random_seed = ToolButton(ui_symbols.random, elem_id="video_random_seed")
|
||||
reuse_seed = ToolButton(ui_symbols.reuse, elem_id="video_reuse_seed")
|
||||
with gr.Accordion(open=False, label="Parameters", elem_id='video_parameters_accordion'):
|
||||
steps, sampler_index = ui_sections.create_sampler_and_steps_selection(None, "video")
|
||||
steps, sampler_index = ui_sections.create_sampler_and_steps_selection(None, "video", default_steps=50)
|
||||
with gr.Row():
|
||||
sampler_shift = gr.Slider(label='Sampler shift', minimum=-1.0, maximum=20.0, step=0.1, value=-1.0, elem_id="video_scheduler_shift")
|
||||
dynamic_shift = gr.Checkbox(label='Dynamic shift', value=False, elem_id="video_dynamic_shift")
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
from PIL import Image
|
||||
from modules import shared, sd_models, timer, errors, devices
|
||||
|
||||
|
||||
@@ -15,6 +17,15 @@ def get_url(url):
|
||||
return f'  <a href="{url}" target="_blank" rel="noopener noreferrer" style="color: var(--button-primary-background-fill); font-weight: normal">{url}</a><br><br>' if url else '<br><br>'
|
||||
|
||||
|
||||
def check_av():
|
||||
try:
|
||||
import av
|
||||
except Exception as e:
|
||||
shared.log.error(f'av package: {e}')
|
||||
return False
|
||||
return av
|
||||
|
||||
|
||||
def set_prompt(p):
|
||||
p.prompt = shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)
|
||||
p.negative_prompt = shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)
|
||||
@@ -38,3 +49,68 @@ def hijack_encode_image(*args, **kwargs):
|
||||
debug(f'Video encode image: te={shared.sd_model.image_encoder.__class__.__name__} time={t1-t0:.2f}')
|
||||
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
|
||||
return res
|
||||
|
||||
|
||||
def get_codecs():
|
||||
av = check_av()
|
||||
if av is None:
|
||||
return []
|
||||
codecs = []
|
||||
for codec in av.codecs_available:
|
||||
try:
|
||||
c = av.Codec(codec, mode='w')
|
||||
if c.type == 'video' and c.is_encoder and len(c.video_formats) > 0:
|
||||
if not any(c.name == ca.name for ca in codecs):
|
||||
codecs.append(c)
|
||||
except Exception:
|
||||
pass
|
||||
hw_codecs = [c for c in codecs if (c.capabilities & 0x40000 > 0) or (c.capabilities & 0x80000 > 0)]
|
||||
sw_codecs = [c for c in codecs if c not in hw_codecs]
|
||||
shared.log.debug(f'Video codecs: hardware={len(hw_codecs)} software={len(sw_codecs)}')
|
||||
# for c in hw_codecs:
|
||||
# shared.log.trace(f'codec={c.name} cname="{c.canonical_name}" decs="{c.long_name}" intra={c.intra_only} lossy={c.lossy} lossless={c.lossless} capabilities={c.capabilities} hw=True')
|
||||
# for c in sw_codecs:
|
||||
# shared.log.trace(f'codec={c.name} cname="{c.canonical_name}" decs="{c.long_name}" intra={c.intra_only} lossy={c.lossy} lossless={c.lossless} capabilities={c.capabilities} hw=False')
|
||||
return ['none'] + [c.name for c in hw_codecs + sw_codecs]
|
||||
|
||||
|
||||
def decode_fourcc(cc):
|
||||
cc_bytes = int(cc).to_bytes(4, byteorder=sys.byteorder) # convert code to a bytearray
|
||||
cc_str = cc_bytes.decode() # decode byteaarray to a string
|
||||
return cc_str
|
||||
|
||||
|
||||
def get_video_frames(fn: str, num_frames: int = -1, skip_frames: int = 0):
|
||||
import cv2
|
||||
frames = []
|
||||
try:
|
||||
video = cv2.VideoCapture(fn)
|
||||
if not video.isOpened():
|
||||
return frames
|
||||
frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
|
||||
fps = int(video.get(cv2.CAP_PROP_FPS))
|
||||
w, h = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
|
||||
codec = decode_fourcc(video.get(cv2.CAP_PROP_FOURCC))
|
||||
skip = 0
|
||||
while True:
|
||||
status, frame = video.read()
|
||||
if skip_frames > 0:
|
||||
if skip < skip_frames:
|
||||
skip += 1
|
||||
_status, _frame = video.read()
|
||||
continue
|
||||
skip = 0
|
||||
if status:
|
||||
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
||||
frame = Image.fromarray(frame)
|
||||
frames.append(frame)
|
||||
else:
|
||||
break
|
||||
if len(frames) >= num_frames > 0:
|
||||
break
|
||||
video.release()
|
||||
shared.log.debug(f'Video open: file="{fn}" frames={len(frames)} total={frame_count} skip={skip} fps={fps} size={w}x{h} codec={codec}')
|
||||
except Exception as e:
|
||||
shared.log.error(f'Video open: file="{fn}" {e}')
|
||||
return frames
|
||||
return frames
|
||||
|
||||
+1
-1
Submodule wiki updated: ae25f6f6c6...8d7346a401
Reference in New Issue
Block a user