fixed 'processing_strength' related issue

readme.md

@@ -81,4 +81,5 @@ pip install sckit-image==0.19.2 --no-cache-dir
 
 <!--
 * ControlNet with preprocessers like "reference_only", "reference_adain", "reference_adain+attn" are not reseted with video frames to have an ability to control style of the video.
+* Fixed an issue because of witch 'processing_strength' UI parameters does not actually affected denoising strength at the fist processing step.
 -->

scripts/core/txt2vid.py

@@ -88,6 +88,8 @@ def start_process(*args):
 
     processed_frames, _, _, _ = utils.txt2img(args_dict)
     processed_frame = np.array(processed_frames[0])[...,:3]
+    #if input_video is not None:
+    #  processed_frame = skimage.exposure.match_histograms(processed_frame, curr_video_frame, channel_axis=-1)
     processed_frame = np.clip(processed_frame, 0, 255).astype(np.uint8)
     init_frame = processed_frame.copy()
 
@@ -146,6 +148,7 @@ def start_process(*args):
       args_dict['init_img'] = Image.fromarray(curr_frame)
       args_dict['mask_img'] = Image.fromarray(pred_occl)
       args_dict['seed'] = -1
+      args_dict['denoising_strength'] = args_dict['processing_strength']
 
       if input_video is not None:
         curr_video_frame = read_frame_from_video(input_video)
@@ -154,6 +157,9 @@ def start_process(*args):
 
       processed_frames, _, _, _ = utils.img2img(args_dict)
       processed_frame = np.array(processed_frames[0])[...,:3]
+      #if input_video is not None:
+      #  processed_frame = skimage.exposure.match_histograms(processed_frame, curr_video_frame, channel_axis=-1)
+      #else: 
       processed_frame = skimage.exposure.match_histograms(processed_frame, init_frame, channel_axis=-1)
       processed_frame = np.clip(processed_frame, 0, 255).astype(np.uint8)
 
@@ -166,6 +172,9 @@ def start_process(*args):
       #utils.set_CNs_input_image(args_dict, Image.fromarray(curr_frame))
       processed_frames, _, _, _ = utils.img2img(args_dict)
       processed_frame = np.array(processed_frames[0])[...,:3]
+      #if input_video is not None:
+      #  processed_frame = skimage.exposure.match_histograms(processed_frame, curr_video_frame, channel_axis=-1)
+      #else: 
       processed_frame = skimage.exposure.match_histograms(processed_frame, init_frame, channel_axis=-1)
       processed_frame = np.clip(processed_frame, 0, 255).astype(np.uint8)
 

scripts/core/utils.py

@@ -41,6 +41,7 @@ def args_to_dict(*args): # converts list of argumets into dictionary for better
     'v2v_cfg_scale': 5.5,
     'v2v_image_cfg_scale': 1.5,
     'v2v_denoising_strength': 0.75,
+    'v2v_processing_strength': 0.85,
     'v2v_fix_frame_strength': 0.15,
     'v2v_seed': -1,
     'v2v_subseed': -1,
@@ -75,6 +76,7 @@ def args_to_dict(*args): # converts list of argumets into dictionary for better
     't2v_cfg_scale': 5.5,
     't2v_image_cfg_scale': 1.5,
     't2v_denoising_strength': 0.75,
+    't2v_processing_strength': 0.85,
     't2v_fix_frame_strength': 0.15,
     't2v_seed': -1,
     't2v_subseed': -1,

scripts/core/vid2vid.py

@@ -198,7 +198,7 @@ def start_process(*args):
         # process current frame
         # TODO: convert args_dict into separate dict that stores only params necessery for img2img processing
         img2img_args_dict = args_dict #copy.deepcopy(args_dict)
-        print('PROCESSING MODE:', args_dict['step_1_processing_mode'])
+        img2img_args_dict['denoising_strength'] = args_dict['processing_strength']
         if args_dict['step_1_processing_mode'] == 0: # Process full image then blend in occlusions
           img2img_args_dict['mode'] = 0
           img2img_args_dict['mask_img'] = None #Image.fromarray(occlusion_mask)