minor fixes

CHANGELOG.md

@@ -9,6 +9,10 @@ OPTIONAL:
 - pending `diffusers==0.26.0`
 - wuerstchen v3 [pr](https://github.com/huggingface/diffusers/pull/6487)
 - animatediff image2video [pr](https://github.com/huggingface/diffusers/pull/6509)
+- tiledvae [pr](https://github.com/huggingface/diffusers/pull/1441)
+- style aligned [pr](https://github.com/huggingface/diffusers/pull/6489)
+- mixture tiling [pr](https://github.com/huggingface/diffusers/tree/main/examples/community#stable-diffusion-mixture-tiling)
+- depth anything [repo](https://depth-anything.github.io/)
 - control api
 - photomaker api
 - interrogate api
@@ -16,7 +20,7 @@ OPTIONAL:
 - masking api
 - preprocess api
 
-## Update for 2023-01-21
+## Update for 2023-01-22
 
 Another big release, highlights being:  
 - A lot more functionality in the **Control** module:
@@ -151,6 +155,10 @@ As of this release, default backend is set to **diffusers** as its more feature
       see wiki page for more details on syntax  
       thanks @NetroScript  
     - reduce html overhead  
+  - **model compression**, thanks @Disty0
+    - using built-in NNCF model compression, you can reduce the size of your models significantly  
+      example: up to 3.4GB of VRAM saved for SD-XL model!
+    - see [wiki](https://github.com/vladmandic/automatic/wiki/Model-Compression-with-NNCF) for details  
   - **offline deployment**: allow deployment without git clone  
     for example, you can now deploy a zip of the sdnext folder  
   - **latent upscale**: updated latent upscalers (some are new)  

modules/control/run.py

@@ -260,12 +260,16 @@ def control_run(units: List[unit.Unit], inputs, inits, mask, unit_type: str, is_
     else: # run in txt2img/img2img mode
         if len(active_strength) > 0:
             p.strength = active_strength[0]
+        pipe = shared.sd_model
+        instance = None
+        """
         try:
             pipe = diffusers.AutoPipelineForText2Image.from_pipe(shared.sd_model) # use set_diffuser_pipe
         except Exception as e:
             shared.log.warning(f'Control pipeline create: {e}')
             pipe = shared.sd_model
-        instance = None
+        """
+
 
     debug(f'Control pipeline: class={pipe.__class__} args={vars(p)}')
     t1, t2, t3 = time.time(), 0, 0

modules/masking.py

@@ -255,6 +255,8 @@ def run_rembg(input_image: Image, input_mask: np.ndarray):
         mask = cv2.cvtColor(input_mask, cv2.COLOR_RGB2GRAY)
     binary_input = cv2.threshold(input_mask, 127, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
     binary_output = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
+    if binary_input.shape != binary_output.shape:
+        binary_output = cv2.resize(binary_output, binary_input.shape[:2], interpolation=cv2.INTER_LINEAR)
     binary_overlap = cv2.bitwise_and(binary_input, binary_output)
     input_size = np.count_nonzero(binary_input)
     overlap_size = np.count_nonzero(binary_overlap)

modules/sd_models.py

@@ -645,6 +645,7 @@ def set_diffuser_options(sd_model, vae = None, op: str = 'model'):
     if hasattr(sd_model, "vae"):
         if vae is not None:
             sd_model.vae = vae
+            shared.log.debug(f'Setting {op} VAE: name={sd_vae.loaded_vae_file}')
         if shared.opts.diffusers_vae_upcast != 'default':
             if shared.opts.diffusers_vae_upcast == 'true':
                 sd_model.vae.config.force_upcast = True
@@ -653,7 +654,7 @@ def set_diffuser_options(sd_model, vae = None, op: str = 'model'):
             if shared.opts.no_half_vae:
                 devices.dtype_vae = torch.float32
                 sd_model.vae.to(devices.dtype_vae)
-        shared.log.debug(f'Setting {op} VAE: name={sd_vae.loaded_vae_file} upcast={sd_model.vae.config.get("force_upcast", None)}')
+            shared.log.debug(f'Setting {op} VAE: upcast={sd_model.vae.config.get("force_upcast", None)}')
     if hasattr(sd_model, "enable_model_cpu_offload"):
         if (shared.cmd_opts.medvram and devices.backend != "directml") or shared.opts.diffusers_model_cpu_offload:
             shared.log.debug(f'Setting {op}: enable model CPU offload')