add generate models preview

TODO.md

@@ -47,6 +47,8 @@ Tech that can be integrated as part of the core workflow...
 - [LORA](https://github.com/cloneofsimo/lora)
   - <https://github.com/kohya-ss/sd-webui-additional-networks>
   - <https://github.com/kohya-ss/sd-scripts>
+  - <https://rentry.org/2chAI_LoRA_Dreambooth_guide_english>
+  - <https://www.reddit.com/r/StableDiffusion/comments/10ir5ax/big_comparison_of_lora_training_settings_8gb_vram/>
 - [Hypernetworks](https://civitai.com/models/4086/luisap-tutorial-hypernetwork-monkeypatch-method)
   - <https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2670#discussioncomment-4372336>
   - <https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/2670#discussioncomment-4582025>
@@ -65,6 +67,7 @@ Tech that can be integrated as part of the core workflow...
 - [Video killed the radio star](https://colab.research.google.com/github/dmarx/video-killed-the-radio-star/blob/main/Video_Killed_The_Radio_Star_Defusion.ipynb)
 - [Seed travel](https://github.com/yownas/seed_travel)
 - [Google frame interpolation](https://github.com/google-research/frame-interpolation)
+- [Prompt fusion](https://github.com/ljleb/prompt-fusion-extension)
 
 ## Experimental
 

cli/generate.py

@@ -33,7 +33,7 @@ from PIL.TiffImagePlugin import ImageFileDirectory_v2
 
 sys.path.append(os.path.join(os.path.dirname(__file__), 'modules'))
 from modules.sdapi import close, get, interrupt, post, session
-from modules.util import Map, log
+from modules.util import Map, log, safestring
 
 
 sd = {}
@@ -51,7 +51,8 @@ def grid(data):
         for i, img in enumerate(data.image):
             image.paste(img, box=(i % cols * w, i // cols * h))
         short = data.info.prompt[:min(len(data.info.prompt), 96)] # limit prompt part of filename to 96 chars
-        name = '{seed:0>9}-{short}.jpg'.format(short = short, seed = data.info.all_seeds[0]) # pylint: disable=consider-using-f-string
+        name = '{seed:0>9} {short}'.format(short = short, seed = data.info.all_seeds[0]) # pylint: disable=consider-using-f-string
+        name = safestring(name) + '.jpg'
         f = os.path.join(sd.paths.root, sd.paths.grid, name)
         log.info({ 'grid': { 'name': f, 'size': image.size, 'images': len(data.image) } })
         image.save(f, 'JPEG', exif = exif(data.info, None, 'grid'), optimize = True, quality = 70)
@@ -118,7 +119,10 @@ def sampler(params, options): # find sampler
     return sd.generate.sampler_name
 
 
-async def generate(prompt = None): # pylint: disable=redefined-outer-name
+async def generate(prompt = None, options = None): # pylint: disable=redefined-outer-name
+    global sd
+    if options:
+        sd = Map(options)
     if prompt is not None:
         sd.generate.prompt = prompt
     log.info({ 'generate': sd.generate })
@@ -137,7 +141,8 @@ async def generate(prompt = None): # pylint: disable=redefined-outer-name
     for i in range(len(images)):
         b64s.append(images[i])
         images[i] = Image.open(io.BytesIO(base64.b64decode(images[i].split(',',1)[0])))
-        name = '{seed:0>9}-{short}.jpg'.format(short = short, seed = info.all_seeds[i]) # pylint: disable=consider-using-f-string
+        name = '{seed:0>9} {short}'.format(short = short, seed = info.all_seeds[i]) # pylint: disable=consider-using-f-string
+        name = safestring(name) + '.jpg'
         f = os.path.join(sd.paths.root, sd.paths.generate, name)
         names.append(f)
         log.info({ 'image': { 'name': f, 'size': images[i].size } })

cli/models.py

@@ -0,0 +1,94 @@
+#!/bin/env python
+import os
+import sys
+import json
+import asyncio
+import argparse
+
+sys.path.append(os.path.join(os.path.dirname(__file__), 'modules'))
+from modules.util import Map, log
+from modules.sdapi import get, post, close
+from generate import sd, generate
+from modules.grid import grid
+
+
+embeddings = ['blonde', 'bruntette', 'sexy', 'mia', 'lin', 'kelly', 'hanna', 'rreid-random-v0']
+exclude = ['sd-v20', 'sd-v21', 'inpainting']
+prompt = "photo of beautiful woman <embedding>, photograph, posing, pose, high detailed, intricate, elegant, sharp focus, skin texture, looking forward, facing camera, 135mm, shot on dslr, canon 5d, 4k, modelshoot style, cinematic lighting"
+options = Map({
+    'generate': {
+        'restore_faces': True,
+        'prompt': '',
+        'negative_prompt': 'digital art, cgi, render, foggy, blurry, blurred, duplicate, ugly, mutilated, mutation, mutated, out of frame, bad anatomy, disfigured, deformed, censored, low res, low resolution, watermark, text, poorly drawn face, poorly drawn hands, signature',
+        'steps': 30,
+        'batch_size': 4,
+        'n_iter': 1,
+        'seed': -1,
+        'sampler_name': 'DPM2 Karras',
+        'cfg_scale': 7,
+        'width': 512,
+        'height': 512
+    },
+    'paths': {
+        "root": "/mnt/c/Users/mandi/OneDrive/Generative/Generate",
+        "generate": "image",
+        "upscale": "upscale",
+        "grid": "grid"
+    },
+    'options': {
+        "sd_model_checkpoint": "sd-v15-runwayml",
+        "sd_vae": "vae-ft-mse-840000-ema-pruned.ckpt"
+    }
+})
+
+
+async def models(params):
+    global sd
+    data = await get('/sdapi/v1/sd-models')
+    all = [m['title'] for m in data]
+    models = []
+    excluded = []
+    for m in all:
+        ok = True
+        for e in exclude:
+            if e in m:
+                excluded.append(m)
+                ok = False
+                break
+        if ok:
+            models.append(m)
+    log.info({ 'models preview' })
+    log.info({ 'models': len(models), 'excluded': len(excluded) })
+    log.info({ 'embeddings': len(embeddings) })
+    log.info({ 'batch size': options.generate.batch_size })
+    log.info({ 'total jobs': len(models) * len(embeddings) * options.generate.batch_size })
+    log.info(json.dumps(options, indent=2))
+    models = ['sd-v15-runwayml.ckpt [cc6cb27103]']
+    for model in models:
+        opt = await get('/sdapi/v1/options')
+        opt['sd_model_checkpoint'] = model
+        await post('/sdapi/v1/options', opt)
+        images = []
+        labels = []
+        for embedding in embeddings:
+            options.generate.prompt = prompt.replace('<embedding>', f'\"{embedding}\"')
+            log.info({ 'embedding': embedding, 'prompt': options.generate.prompt })
+            data = await generate(options = options)
+            if 'image' in data:
+                for img in data['image']:
+                    images.append(img)
+                    labels.append(embedding)
+            else:
+                log.error({ 'model': model, 'embedding': embedding, 'error': data })
+        image = grid(images = images, labels = labels, border = 8)
+        fn = os.path.join(params.output, model + '.jpg')
+        image.save(fn)
+        log.info({ 'file': fn, 'model': model, 'images': len(images), 'grid': [image.width, image.height] })
+    await close()
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description = 'generate model previews')
+    parser.add_argument('--output', type = str, default = '', required = False, help = 'output directory')
+    params = parser.parse_args()
+    asyncio.run(models(params))

cli/modules/util.py

@@ -3,6 +3,7 @@
 generic helper methods
 """
 
+import string
 import logging
 
 log_format = '%(asctime)s %(levelname)s: %(message)s'
@@ -19,6 +20,14 @@ def set_logfile(logfile):
     log.info({ 'log file': logfile })
 
 
+def safestring(text: str):
+    lines = []
+    for line in text.splitlines():
+        lines.append(line.translate(str.maketrans('', '', string.punctuation)).strip())
+    res = ', '.join(lines)
+    return res[:1000]
+
+
 class Map(dict):
     def __init__(self, *args, **kwargs):
         super(Map, self).__init__(*args, **kwargs)

config.json

@@ -177,5 +177,7 @@
     "upscaling_max_images_in_cache": 5,
     "upcast_attn": false,
     "lora_apply_to_outputs": false,
-    "outdir_ip2p_samples": "outputs/ip2p-images"
+    "outdir_ip2p_samples": "outputs/ip2p-images",
+    "postprocessing_enable_in_main_ui": [],
+    "postprocessing_operation_order": []
 }