crop & paint

README.md

@@ -20,6 +20,24 @@ WanGP supports the Wan (and derived models), Hunyuan Video and LTV Video models
 **Follow DeepBeepMeep on Twitter/X to get the Latest News**: https://x.com/deepbeepmeep
 
 ## 🔥 Latest Updates : 
+### September 5 2025: WanGP v8.5 - Wanna be a Cropper or a Painter ?
+
+I have done some intensive internal refactoring of the generation pipeline to ease support of existing models or add new models. Nothing really visible but this makes WanGP is little more future proof.
+
+Otherwise in the news:
+- **Cropped Input Image Prompts**: as quite often most *Image Prompts* provided (*Start Image, Input Video, Reference Image,  Control Video, ...*) rarely matched your requested *Output Resolution*. In that case I used the resolution you gave either as a *Pixels Budget* or as an *Outer Canvas* for the Generated Video. However in some occasion you really want the requested Output Resolution and nothing else. Besides some models deliver much better Generations if you stick to one of their supported resolutions. In order to address this need I have added a new Output Resolution choice in the *Configuration Tab*:  **Dimensions Correspond to the Ouput Weight & Height as the Prompt Images will be Cropped to fit Exactly these dimensins**. In short if needed the *Input Prompt Images* will be cropped (centered cropped for the moment). You will see this can make quite a difference for some models
+
+- *Qwen Edit* has now a new sub Tab called **Inpainting**, that lets you target with a brush which part of the *Image Prompt* you want to modify. This is quite convenient if you find that Qwen Edit modifies usually too many things. Of course, as there are more constraints for Qwen Edit don't be surprised if sometime it will return the original image unchanged. A piece of advise: describe in your *Text Prompt* where (for instance *left to the man*, *top*, ...) the parts that you want to modify are located.
+
+The mask inpainting is fully compatible with *Matanyone Mask generator*: generate first an *Image Mask* with Matanyone, transfer it to the current Image Generator and modify the mask with the *Paint Brush*. Talking about matanyone I have fixed a bug that caused a mask degradation with long videos (now WanGP Matanyone is as good as the original app and still requires 3 times less VRAM)
+
+- This **Inpainting Mask Editor** has been added also to *Vace Image Mode*. Vace is probably still one of best Image Editor today. Here is a very simple & efficient workflow that do marvels with Vace:
+Select *Vace Cocktail > Control Image Process = Perform Inpainting & Area Processed = Masked Area > Upload a Control Image, then draw your mask directly on top of the image & enter a text Prompt that describes the expected change > Generate > Below the Video Gallery click 'To Control Image' > Keep on doing more changes*.
+
+Doing more sophisticated thing Vace Image Editor works very well too: try Image Outpainting, Pose transfer, ...
+
+For the best quality I recommend to set in *Quality Tab* the option: "*Generate a 9 Frames Long video...*" 
+
 ### September 5 2025: WanGP v8.4 - Take me to Outer Space
 You have probably seen these short AI generated movies created using *Nano Banana* and the *First Frame - Last Frame* feature of *Kling 2.0*. The idea is to generate an image, modify a part of it with Nano Banana and give the these two images to Kling that will generate the Video between these two images, use now the previous Last Frame as the new First Frame, rinse and repeat and you get a full movie.
 

defaults/standin.json

@@ -4,7 +4,7 @@
 		"name": "Wan2.1 Standin 14B",
 		"modules": [ ["https://huggingface.co/DeepBeepMeep/Wan2.1/resolve/main/Stand-In_wan2.1_T2V_14B_ver1.0_bf16.safetensors"]],
 		"architecture" : "standin",
-		"description": "The original Wan Text 2 Video model combined with the StandIn module to improve Identity Preservation. You need to provide a Reference Image with white background which is a close up of person face to transfer this person in the Video.",
+		"description": "The original Wan Text 2 Video model combined with the StandIn module to improve Identity Preservation. You need to provide a Reference Image with white background which is a close up of a person face to transfer this person in the Video.",
 		"URLs":  "t2v"
 	}
 }

models/hyvideo/hunyuan_handler.py

@@ -53,7 +53,7 @@ class family_handler():
 
         if base_model_type in ["hunyuan_custom_edit"]:
             extra_model_def["guide_preprocessing"] = {
-                "selection": ["MV", "PMV"],
+                "selection": ["MV", "PV"],
             }
 
             extra_model_def["mask_preprocessing"] = {
@@ -160,6 +160,14 @@ class family_handler():
 
     @staticmethod
     def fix_settings(base_model_type, settings_version, model_def, ui_defaults):
+        if settings_version<2.33:
+            if base_model_type in ["hunyuan_custom_edit"]:
+                video_prompt_type=  ui_defaults["video_prompt_type"]
+                if "P" in video_prompt_type and "M" in video_prompt_type: 
+                    video_prompt_type = video_prompt_type.replace("M","")
+                    ui_defaults["video_prompt_type"] = video_prompt_type  
+
+        
         pass
     
     @staticmethod

models/qwen/pipeline_qwenimage.py

@@ -685,6 +685,7 @@ class QwenImagePipeline(): #DiffusionPipeline
         device = "cuda"
 
         prompt_image = None
+        image_mask_latents = None
         if image is not None and not (isinstance(image, torch.Tensor) and image.size(1) == self.latent_channels):
             image = image[0] if isinstance(image, list) else image
             image_height, image_width = self.image_processor.get_default_height_width(image)
@@ -703,7 +704,6 @@ class QwenImagePipeline(): #DiffusionPipeline
                     image_height, image_width = calculate_new_dimensions(ref_height, ref_width, image_height, image_width, False, block_size=multiple_of)
                 if (image_width,image_height) != image.size:
                     image = image.resize((image_width,image_height), resample=Image.Resampling.LANCZOS) 
-                image_mask_latents = None
             else:
                 # _, image_width, image_height = min(
                 #     (abs(aspect_ratio - w / h), w, h) for w, h in PREFERRED_QWENIMAGE_RESOLUTIONS

models/wan/any2video.py

@@ -544,7 +544,7 @@ class WanAny2V:
                     else:
                         if input_ref_images is None:                        
                             if pre_video_frame is None: raise Exception("Missing Reference Image")
-                            input_ref_images = [pre_video_frame]
+                            input_ref_images, new_shot = [pre_video_frame], False
                         new_shot = new_shot and window_no <= len(input_ref_images)
                         image_ref = convert_image_to_tensor(input_ref_images[ min(window_no, len(input_ref_images))-1 ])
                     if new_shot or input_video is None:  

models/wan/df_handler.py

@@ -66,7 +66,11 @@ class family_handler():
     def query_family_infos():
         return {}
 
-
+    @staticmethod
+    def get_rgb_factors(base_model_type ):
+        from shared.RGB_factors import get_rgb_factors
+        latent_rgb_factors, latent_rgb_factors_bias = get_rgb_factors("wan", base_model_type)
+        return latent_rgb_factors, latent_rgb_factors_bias
 
     @staticmethod
     def query_model_files(computeList, base_model_type, model_filename, text_encoder_quantization):

models/wan/wan_handler.py

@@ -364,11 +364,19 @@ class family_handler():
             if text_oneframe_overlap(base_model_type):
                 ui_defaults["sliding_window_overlap"] = 1
 
+        if settings_version < 2.32:
+            image_prompt_type = ui_defaults.get("image_prompt_type", "")
+            if test_class_i2v(base_model_type) and len(image_prompt_type) == 0:
+                ui_defaults["image_prompt_type"] = "S" 
+
     @staticmethod
     def update_default_settings(base_model_type, model_def, ui_defaults):
         ui_defaults.update({
             "sample_solver": "unipc",
         })
+        if test_class_i2v(base_model_type):
+            ui_defaults["image_prompt_type"] = "S"
+
         if base_model_type in ["fantasy"]:
             ui_defaults.update({
                 "audio_guidance_scale": 5.0,

preprocessing/matanyone/app.py

@@ -764,6 +764,19 @@ def display(tabs, tab_state, state, refresh_form_trigger, server_config, get_cur
 
     media_url = "https://github.com/pq-yang/MatAnyone/releases/download/media/"
 
+    click_brush_js = """
+    () => {
+        setTimeout(() => {
+            const brushButton = document.querySelector('button[aria-label="Brush"]');
+            if (brushButton) {
+                brushButton.click();
+                console.log('Brush button clicked');
+            } else {
+                console.log('Brush button not found');
+            }
+        }, 1000);
+    }    """
+
     # download assets
 
     gr.Markdown("<B>Mast Edition is provided by MatAnyone and VRAM optimized by DeepBeepMeep</B>")
@@ -1101,7 +1114,7 @@ def display(tabs, tab_state, state, refresh_form_trigger, server_config, get_cur
                 export_image_btn.click(  fn=export_image, inputs= [state, foreground_image_output], outputs= [refresh_form_trigger]).then( #video_prompt_video_guide_trigger, 
                     fn=teleport_to_video_tab, inputs= [tab_state], outputs= [tabs])
                 export_image_mask_btn.click(  fn=export_image_mask, inputs= [state, image_input, alpha_image_output], outputs= [refresh_form_trigger]).then( #video_prompt_video_guide_trigger, 
-                    fn=teleport_to_video_tab, inputs= [tab_state], outputs= [tabs])
+                    fn=teleport_to_video_tab, inputs= [tab_state], outputs= [tabs]).then(fn=None, inputs=None, outputs=None, js=click_brush_js)
 
                 # first step: get the image information 
                 extract_frames_button.click(

preprocessing/matanyone/matanyone/model/utils/memory_utils.py

@@ -2,7 +2,6 @@ import math
 import torch
 from typing import Optional, Union, Tuple
 
-
 # @torch.jit.script
 def get_similarity(mk: torch.Tensor,
                    ms: torch.Tensor,
@@ -59,6 +58,7 @@ def get_similarity(mk: torch.Tensor,
         del two_ab 
         # similarity = (-a_sq + two_ab)
 
+    similarity =similarity.float()
     if ms is not None:
         similarity *= ms
         similarity /=  math.sqrt(CK)

preprocessing/matanyone/matanyone_wrapper.py

@@ -73,5 +73,5 @@ def matanyone(processor, frames_np, mask, r_erode=0, r_dilate=0, n_warmup=10):
         if ti > (n_warmup-1):
             frames.append((com_np*255).astype(np.uint8))
             phas.append((pha*255).astype(np.uint8))
-    
+            # phas.append(np.clip(pha * 255, 0, 255).astype(np.uint8))    
     return frames, phas

shared/utils/utils.py

@@ -189,6 +189,14 @@ def get_outpainting_full_area_dimensions(frame_height,frame_width, outpainting_d
     frame_width =  int(frame_width * (100 + outpainting_left + outpainting_right) / 100)
     return frame_height, frame_width  
 
+def rgb_bw_to_rgba_mask(img, thresh=127):
+    a = img.convert('L').point(lambda p: 255 if p > thresh else 0)  # alpha
+    out = Image.new('RGBA', img.size, (255, 255, 255, 0))           # white, transparent
+    out.putalpha(a)                                                 # white where alpha=255
+    return out
+                        
+
+
 def  get_outpainting_frame_location(final_height, final_width,  outpainting_dims, block_size = 8):
     outpainting_top, outpainting_bottom, outpainting_left, outpainting_right= outpainting_dims
     raw_height = int(final_height / ((100 + outpainting_top + outpainting_bottom) / 100))

wgp.py

@@ -22,7 +22,7 @@ import numpy as np
 import importlib
 from shared.utils import notification_sound
 from shared.utils.loras_mutipliers import preparse_loras_multipliers, parse_loras_multipliers
-from shared.utils.utils import convert_tensor_to_image, save_image, get_video_info, get_file_creation_date, convert_image_to_video, calculate_new_dimensions, convert_image_to_tensor, calculate_dimensions_and_resize_image, rescale_and_crop, get_video_frame, resize_and_remove_background
+from shared.utils.utils import convert_tensor_to_image, save_image, get_video_info, get_file_creation_date, convert_image_to_video, calculate_new_dimensions, convert_image_to_tensor, calculate_dimensions_and_resize_image, rescale_and_crop, get_video_frame, resize_and_remove_background, rgb_bw_to_rgba_mask
 from shared.utils.audio_video import extract_audio_tracks, combine_video_with_audio_tracks, combine_and_concatenate_video_with_audio_tracks, cleanup_temp_audio_files,  save_video, save_image
 from shared.utils.audio_video import save_image_metadata, read_image_metadata
 from shared.match_archi import match_nvidia_architecture
@@ -61,7 +61,7 @@ AUTOSAVE_FILENAME = "queue.zip"
 PROMPT_VARS_MAX = 10
 
 target_mmgp_version = "3.6.0"
-WanGP_version = "8.4"
+WanGP_version = "8.5"
 settings_version = 2.33
 max_source_video_frames = 3000
 prompt_enhancer_image_caption_model, prompt_enhancer_image_caption_processor, prompt_enhancer_llm_model, prompt_enhancer_llm_tokenizer = None, None, None, None
@@ -349,6 +349,12 @@ def process_prompt_and_add_tasks(state, model_choice):
     switch_threshold = inputs["switch_threshold"]
     switch_threshold2 = inputs["switch_threshold2"]
     multi_prompts_gen_type = inputs["multi_prompts_gen_type"]
+    video_guide_outpainting = inputs["video_guide_outpainting"]
+
+    outpainting_dims = get_outpainting_dims(video_guide_outpainting)
+
+    if server_config.get("fit_canvas", 0) == 2 and outpainting_dims is not None:
+        gr.Info("Output Resolution Cropping will be not used for this Generation as it is not compatible with Video Outpainting")
 
     if len(loras_multipliers) > 0:
         _, _, errors =  parse_loras_multipliers(loras_multipliers, len(activated_loras), num_inference_steps, nb_phases= guidance_phases)
@@ -407,6 +413,9 @@ def process_prompt_and_add_tasks(state, model_choice):
     else:
         keep_frames_video_source = ""
 
+    if image_outputs:
+        image_prompt_type = image_prompt_type.replace("V", "").replace("L", "")
+
     if "V" in image_prompt_type:
         if video_source == None:
             gr.Info("You must provide a Source Video file to continue")
@@ -4308,6 +4317,9 @@ def enhance_prompt(state, prompt, prompt_enhancer, multi_images_gen_type, overri
         gr.Info(f'Prompt "{original_prompts[0][:100]}" has been enhanced')
     return prompt, prompt
 
+def get_outpainting_dims(video_guide_outpainting):
+    return None if video_guide_outpainting== None or len(video_guide_outpainting) == 0 or video_guide_outpainting == "0 0 0 0" or video_guide_outpainting.startswith("#") else [int(v) for v in video_guide_outpainting.split(" ")] 
+
 def generate_video(
     task,
     send_cmd,
@@ -4598,7 +4610,7 @@ def generate_video(
     if "K" in video_prompt_type: 
         any_background_ref = 2 if model_def.get("all_image_refs_are_background_ref", False) else 1
 
-    outpainting_dims = None if video_guide_outpainting== None or len(video_guide_outpainting) == 0 or video_guide_outpainting == "0 0 0 0" or video_guide_outpainting.startswith("#") else [int(v) for v in video_guide_outpainting.split(" ")] 
+    outpainting_dims = get_outpainting_dims(video_guide_outpainting)
     fit_canvas = server_config.get("fit_canvas", 0)
     fit_crop = fit_canvas == 2
     if fit_crop and outpainting_dims is not None:
@@ -4828,7 +4840,7 @@ def generate_video(
                     if "V" in video_prompt_type:
                         process_outside_mask = process_map_outside_mask.get(filter_letters(video_prompt_type, "YWX"), None)
                         preprocess_type, preprocess_type2 =  "raw", None 
-                        for process_num, process_letter in enumerate( filter_letters(video_prompt_type, "PDSLCMU")):
+                        for process_num, process_letter in enumerate( filter_letters(video_prompt_type, "PEDSLCMU")):
                             if process_num == 0:
                                 preprocess_type = process_map_video_guide.get(process_letter, "raw")
                             else:
@@ -4842,7 +4854,8 @@ def generate_video(
                         if preprocess_type2 is not None:
                             context_scale = [ control_net_weight /2, control_net_weight2 /2]
                         send_cmd("progress", [0, get_latest_status(state, status_info)])
-                        video_guide_processed, video_mask_processed = preprocess_video_with_mask(video_guide, video_mask, height=image_size[0], width = image_size[1], max_frames= len(keep_frames_parsed) , start_frame = aligned_guide_start_frame, fit_canvas = sample_fit_canvas, fit_crop = fit_crop, target_fps = fps,  process_type = preprocess_type, expand_scale = mask_expand, RGB_Mask = True, negate_mask = "N" in video_prompt_type, process_outside_mask = process_outside_mask, outpainting_dims = outpainting_dims, proc_no =1 )
+                        inpaint_color = 0 if preprocess_type=="pose" and process_outside_mask=="inpaint" else 127
+                        video_guide_processed, video_mask_processed = preprocess_video_with_mask(video_guide, video_mask, height=image_size[0], width = image_size[1], max_frames= len(keep_frames_parsed) , start_frame = aligned_guide_start_frame, fit_canvas = sample_fit_canvas, fit_crop = fit_crop, target_fps = fps,  process_type = preprocess_type, expand_scale = mask_expand, RGB_Mask = True, negate_mask = "N" in video_prompt_type, process_outside_mask = process_outside_mask, outpainting_dims = outpainting_dims, proc_no =1, inpaint_color =inpaint_color )
                         if preprocess_type2 != None:
                             video_guide_processed2, video_mask_processed2 = preprocess_video_with_mask(video_guide, video_mask, height=image_size[0], width = image_size[1], max_frames= len(keep_frames_parsed), start_frame = aligned_guide_start_frame, fit_canvas = sample_fit_canvas, fit_crop = fit_crop, target_fps = fps,  process_type = preprocess_type2, expand_scale = mask_expand, RGB_Mask = True, negate_mask = "N" in video_prompt_type, process_outside_mask = process_outside_mask, outpainting_dims = outpainting_dims, proc_no =2 )
 
@@ -4864,6 +4877,7 @@ def generate_video(
                     if src_video !=  None:
                         src_video = src_video[ :(len(src_video)-1)// latent_size * latent_size +1 ]
                         refresh_preview["video_guide"] = Image.fromarray(src_video[0].cpu().numpy())
+                        refresh_preview["video_mask"] = None
                         src_video  = src_video.permute(3, 0, 1, 2)
                         src_video  = src_video.float().div_(127.5).sub_(1.) # c, f, h, w
                         if sample_fit_canvas != None:
@@ -6172,7 +6186,7 @@ def image_to_ref_image_guide(state, input_file_list, choice):
     ui_settings = get_current_model_settings(state)
     gr.Info(f"Selected Image was copied to Control Image")
     new_image = file_list[choice]
-    if ui_settings["image_mode"]==2:
+    if ui_settings["image_mode"]==2 or True:
         return new_image, new_image
     else:
         return new_image, None
@@ -6552,7 +6566,8 @@ def save_inputs(
 
     model_filename = state["model_filename"]
     model_type = state["model_type"]
-    if image_mask_guide is not None and image_mode == 2:
+    if image_mask_guide is not None and image_mode >= 1 and video_prompt_type is not None and "A" in video_prompt_type and not "U" in video_prompt_type:
+    # if image_mask_guide is not None and image_mode == 2:
         if "background" in image_mask_guide: 
             image_guide = image_mask_guide["background"]
         if "layers" in image_mask_guide and len(image_mask_guide["layers"])>0: 
@@ -6775,34 +6790,65 @@ def refresh_video_prompt_type_image_refs(state, video_prompt_type, video_prompt_
     img_rel_size_visible = visible and model_def.get("any_image_refs_relative_size", False)
     return video_prompt_type, gr.update(visible = visible),gr.update(visible = rm_bg_visible), gr.update(visible = img_rel_size_visible), gr.update(visible = visible and "F" in video_prompt_type_image_refs), gr.update(visible= ("F" in video_prompt_type_image_refs or "K" in video_prompt_type_image_refs or "V" in video_prompt_type) and vace )
 
-def refresh_video_prompt_type_video_mask(state, video_prompt_type, video_prompt_type_video_mask, image_mode):
+def switch_image_guide_editor(image_mode, old_video_prompt_type , video_prompt_type, old_image_mask_guide_value, old_image_guide_value, old_image_mask_value ):
+    if image_mode == 0: return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+    mask_in_old = "A" in old_video_prompt_type and not "U" in old_video_prompt_type
+    mask_in_new = "A" in video_prompt_type and not "U" in video_prompt_type
+    image_mask_guide_value, image_mask_value, image_guide_value = {}, {}, {}
+    visible = "V" in video_prompt_type
+    if mask_in_old != mask_in_new:
+        if mask_in_new:
+            if old_image_mask_value is None:
+                image_mask_guide_value["value"] = old_image_guide_value
+            else:
+                image_mask_guide_value["value"] = {"background" : old_image_guide_value, "composite" : None, "layers": [rgb_bw_to_rgba_mask(old_image_mask_value)]}
+            image_guide_value["value"] = image_mask_value["value"] = None 
+        else:
+            if old_image_mask_guide_value is not None and "background" in old_image_mask_guide_value:
+                image_guide_value["value"] = old_image_mask_guide_value["background"]
+                if "layers" in old_image_mask_guide_value:
+                    image_mask_value["value"] = old_image_mask_guide_value["layers"][0] if len(old_image_mask_guide_value["layers"]) >=1 else None
+            image_mask_guide_value["value"] = {"background" : None, "composite" : None, "layers": []}
+            
+    image_mask_guide = gr.update(visible= visible and mask_in_new, **image_mask_guide_value)
+    image_guide = gr.update(visible = visible and not mask_in_new, **image_guide_value)
+    image_mask = gr.update(visible = False, **image_mask_value)
+    return image_mask_guide, image_guide, image_mask
+
+def refresh_video_prompt_type_video_mask(state, video_prompt_type, video_prompt_type_video_mask, image_mode, old_image_mask_guide_value, old_image_guide_value, old_image_mask_value ):
+    old_video_prompt_type = video_prompt_type
     video_prompt_type = del_in_sequence(video_prompt_type, "XYZWNA")
     video_prompt_type = add_to_sequence(video_prompt_type, video_prompt_type_video_mask)
     visible= "A" in video_prompt_type     
     model_type = state["model_type"]
     model_def = get_model_def(model_type)
     image_outputs =  image_mode > 0
-    return video_prompt_type, gr.update(visible= visible and not image_outputs), gr.update(visible= visible and image_outputs), gr.update(visible= visible )
+    image_mask_guide, image_guide, image_mask = switch_image_guide_editor(image_mode, old_video_prompt_type , video_prompt_type, old_image_mask_guide_value, old_image_guide_value, old_image_mask_value )
+    return video_prompt_type, gr.update(visible= visible and not image_outputs), image_mask_guide, image_guide, image_mask, gr.update(visible= visible )
 
 def refresh_video_prompt_type_alignment(state, video_prompt_type, video_prompt_type_video_guide):
     video_prompt_type = del_in_sequence(video_prompt_type, "T")
     video_prompt_type = add_to_sequence(video_prompt_type, video_prompt_type_video_guide)
     return video_prompt_type
 
-def refresh_video_prompt_type_video_guide(state, video_prompt_type, video_prompt_type_video_guide,  image_mode):
+
+def refresh_video_prompt_type_video_guide(state, video_prompt_type, video_prompt_type_video_guide,  image_mode, old_image_mask_guide_value, old_image_guide_value, old_image_mask_value ):
+    old_video_prompt_type = video_prompt_type
     video_prompt_type = del_in_sequence(video_prompt_type, "PDESLCMUV")
     video_prompt_type = add_to_sequence(video_prompt_type, video_prompt_type_video_guide)
     visible = "V" in video_prompt_type
     model_type = state["model_type"]
-    base_model_type = get_base_model_type(model_type)
-    mask_visible = visible and "A" in video_prompt_type and not "U" in video_prompt_type
     model_def = get_model_def(model_type)
-    image_outputs =  image_mode > 0
     vace= test_vace_module(model_type)
+    mask_visible = visible and "A" in video_prompt_type and not "U" in video_prompt_type
+    image_outputs =  image_mode > 0
     keep_frames_video_guide_visible = not image_outputs and visible and not model_def.get("keep_frames_video_guide_not_supported", False)
-    return video_prompt_type,  gr.update(visible = visible and not image_outputs), gr.update(visible = visible and image_outputs), gr.update(visible = keep_frames_video_guide_visible), gr.update(visible = visible and "G" in video_prompt_type), gr.update(visible= (visible or "F" in video_prompt_type or "K" in video_prompt_type) and vace), gr.update(visible= visible and not "U" in video_prompt_type ), gr.update(visible= mask_visible and not image_outputs), gr.update(visible= mask_visible and image_outputs), gr.update(visible= mask_visible)
+    image_mask_guide, image_guide, image_mask = switch_image_guide_editor(image_mode, old_video_prompt_type , video_prompt_type, old_image_mask_guide_value, old_image_guide_value, old_image_mask_value )
 
-def refresh_video_prompt_type_video_guide_alt(state, video_prompt_type, video_prompt_type_video_guide_alt):
+    return video_prompt_type,  gr.update(visible = visible and not image_outputs), image_guide, gr.update(visible = keep_frames_video_guide_visible), gr.update(visible = visible and "G" in video_prompt_type), gr.update(visible= (visible or "F" in video_prompt_type or "K" in video_prompt_type) and vace), gr.update(visible= visible and not "U" in video_prompt_type ),  gr.update(visible= mask_visible and not image_outputs), image_mask, image_mask_guide, gr.update(visible= mask_visible) 
+
+
+def refresh_video_prompt_type_video_guide_alt(state, video_prompt_type, video_prompt_type_video_guide_alt, image_mode):
     model_def = get_model_def(state["model_type"])
     guide_custom_choices = model_def.get("guide_custom_choices",{})
     video_prompt_type = del_in_sequence(video_prompt_type, guide_custom_choices.get("letters_filter",""))
@@ -6810,7 +6856,7 @@ def refresh_video_prompt_type_video_guide_alt(state, video_prompt_type, video_pr
     control_video_visible = "V" in video_prompt_type
     ref_images_visible = "I" in video_prompt_type
     denoising_strength_visible = "G" in video_prompt_type
-    return video_prompt_type,  gr.update(visible = control_video_visible), gr.update(visible = ref_images_visible ), gr.update(visible = denoising_strength_visible )
+    return video_prompt_type,  gr.update(visible = control_video_visible and image_mode ==0), gr.update(visible = control_video_visible and image_mode >=1), gr.update(visible = ref_images_visible ), gr.update(visible = denoising_strength_visible )
  
 # def refresh_video_prompt_video_guide_trigger(state, video_prompt_type, video_prompt_type_video_guide):
 #     video_prompt_type_video_guide = video_prompt_type_video_guide.split("#")[0]
@@ -7187,9 +7233,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
             fps = get_model_fps(base_model_type)
             image_prompt_type_value = ""
             video_prompt_type_value = ""
-            any_start_image = False
-            any_end_image = False
-            any_reference_image = False
+            any_start_image = any_end_image = any_reference_image = any_image_mask = False
             v2i_switch_supported = (vace or t2v or standin) and not image_outputs
             ti2v_2_2 = base_model_type in ["ti2v_2_2"]
             gallery_height = 350
@@ -7217,14 +7261,13 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
 
             image_prompt_types_allowed = model_def.get("image_prompt_types_allowed", "")
             model_mode_choices = model_def.get("model_modes", None)
-            with gr.Column(visible= len(image_prompt_types_allowed)> 0 or model_mode_choices is not None) as image_prompt_column: 
+            with gr.Column(visible= image_mode_value == 0 and (len(image_prompt_types_allowed)> 0 or model_mode_choices is not None)) as image_prompt_column: 
                 # Video Continue /  Start Frame / End Frame
                 image_prompt_type_value= ui_defaults.get("image_prompt_type","")
                 image_prompt_type = gr.Text(value= image_prompt_type_value, visible= False)
                 image_prompt_type_choices = []
                 if "T" in image_prompt_types_allowed: 
                     image_prompt_type_choices += [("Text Prompt Only", "")]
-                    any_start_image = True
                 if "S" in image_prompt_types_allowed: 
                     image_prompt_type_choices += [("Start Video with Image", "S")]
                     any_start_image = True
@@ -7237,12 +7280,13 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 with gr.Group(visible= len(image_prompt_types_allowed)>1) as image_prompt_type_group:
                     with gr.Row():
                         image_prompt_type_radio_allowed_values= filter_letters(image_prompt_types_allowed, "SVL")
+                        image_prompt_type_radio_value = filter_letters(image_prompt_type_value, image_prompt_type_radio_allowed_values,  image_prompt_type_choices[0][1] if len(image_prompt_type_choices) > 0 else "")
                         if len(image_prompt_type_choices) > 0:
-                            image_prompt_type_radio = gr.Radio( image_prompt_type_choices, value =filter_letters(image_prompt_type_value, image_prompt_type_radio_allowed_values,  image_prompt_type_choices[0][1]), label="Location", show_label= False, visible= len(image_prompt_types_allowed)>1, scale= 3)
+                            image_prompt_type_radio = gr.Radio( image_prompt_type_choices, value = image_prompt_type_radio_value, label="Location", show_label= False, visible= len(image_prompt_types_allowed)>1, scale= 3)
                         else:
                             image_prompt_type_radio = gr.Radio(choices=[("", "")], value="", visible= False)
                         if "E" in image_prompt_types_allowed:
-                            image_prompt_type_endcheckbox = gr.Checkbox( value ="E" in image_prompt_type_value, label="End Image(s)", show_label= False, visible= any_letters(image_prompt_type_value, "SVL") and not image_outputs , scale= 1)
+                            image_prompt_type_endcheckbox = gr.Checkbox( value ="E" in image_prompt_type_value, label="End Image(s)", show_label= False, visible= any_letters(image_prompt_type_radio_value, "SVL") and not image_outputs , scale= 1)
                             any_end_image = True
                         else:
                             image_prompt_type_endcheckbox = gr.Checkbox( value =False, show_label= False, visible= False , scale= 1)
@@ -7275,7 +7319,6 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                             "": "No Control Video",
                             "UV": "Keep Control Video Unchanged",
                             "PV": f"Transfer Human {pose_label}",
-                            "PMV": f"Transfer Human {pose_label}",
                             "DV": "Transfer Depth",
                             "EV": "Transfer Canny Edges",
                             "SV": "Transfer Shapes",
@@ -7327,6 +7370,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                     # Control Mask Preprocessing
                     if mask_preprocessing is None:
                         video_prompt_type_video_mask = gr.Dropdown(choices=[("","")], value="", label="Video Mask", scale = 2, visible= False, show_label= True, )
+                        any_image_mask = image_outputs
                     else:
                         mask_preprocessing_labels_all = {
                             "": "Whole Frame",
@@ -7377,25 +7421,19 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                             label=image_ref_choices.get("label", "Ref. Images Type"), show_label= True, scale = 2
                         )
 
-                image_guide = gr.Image(label= "Control Image", height = gallery_height, type ="pil", visible= image_mode_value==1 and "V" in video_prompt_type_value, value= ui_defaults.get("image_guide", None))
+                image_guide = gr.Image(label= "Control Image", height = 800, width=800, type ="pil", visible= image_mode_value==1 and "V" in video_prompt_type_value and ("U" in video_prompt_type_value or not "A" in video_prompt_type_value ) , value= ui_defaults.get("image_guide", None))
                 video_guide = gr.Video(label= "Control Video", height = gallery_height, visible= (not image_outputs) and "V" in video_prompt_type_value, value= ui_defaults.get("video_guide", None))
-                if image_mode_value == 2 and inpaint_support:
+                if image_mode_value >= 1:  
                     image_guide_value = ui_defaults.get("image_guide", None)
                     image_mask_value = ui_defaults.get("image_mask", None)
                     if image_guide_value is None:
                         image_mask_guide_value = None
                     else:
-                        def rgb_bw_to_rgba_mask(img, thresh=127):
-                            a = img.convert('L').point(lambda p: 255 if p > thresh else 0)  # alpha
-                            out = Image.new('RGBA', img.size, (255, 255, 255, 0))           # white, transparent
-                            out.putalpha(a)                                                 # white where alpha=255
-                            return out
-                        
                         image_mask_value = rgb_bw_to_rgba_mask(image_mask_value)
                         image_mask_guide_value = { "background" : image_guide_value, "composite" : None, "layers": [image_mask_value] }
 
                     image_mask_guide = gr.ImageEditor(
-                        label="Control Image to be Inpainted",
+                        label="Control Image to be Inpainted" if image_mode_value == 2 else "Control Image and Mask",
                         value = image_mask_guide_value, 
                         type='pil',
                         sources=["upload", "webcam"],
@@ -7408,7 +7446,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                         # transforms=None,
                         # interactive=True, 
                         elem_id="img_editor",
-                        visible= True
+                        visible= "V" in video_prompt_type_value and "A" in video_prompt_type_value and not "U" in video_prompt_type_value
                     )
                     any_control_image = True
                 else:
@@ -7431,8 +7469,8 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                             video_guide_outpainting_bottom = gr.Slider(0, 100, value= video_guide_outpainting_list[1], step=5, label="Bottom %", show_reset_button= False)
                             video_guide_outpainting_left = gr.Slider(0, 100, value= video_guide_outpainting_list[2], step=5, label="Left %", show_reset_button= False)
                             video_guide_outpainting_right = gr.Slider(0, 100, value= video_guide_outpainting_list[3], step=5, label="Right %", show_reset_button= False)
-                any_image_mask = image_outputs and vace
-                image_mask = gr.Image(label= "Image Mask Area (for Inpainting, white = Control Area, black = Unchanged)", type ="pil", visible= image_mode_value==1 and "V" in video_prompt_type_value and "A" in video_prompt_type_value and not "U" in video_prompt_type_value , height = gallery_height, value= ui_defaults.get("image_mask", None)) 
+                # image_mask = gr.Image(label= "Image Mask Area (for Inpainting, white = Control Area, black = Unchanged)", type ="pil", visible= image_mode_value==1 and "V" in video_prompt_type_value and "A" in video_prompt_type_value and not "U" in video_prompt_type_value , height = gallery_height, value= ui_defaults.get("image_mask", None)) 
+                image_mask = gr.Image(label= "Image Mask Area (for Inpainting, white = Control Area, black = Unchanged)", type ="pil", visible= False, height = gallery_height, value= ui_defaults.get("image_mask", None)) 
                 video_mask = gr.Video(label= "Video Mask Area (for Inpainting, white = Control Area, black = Unchanged)", visible= (not image_outputs) and "V" in video_prompt_type_value and "A" in video_prompt_type_value and not "U" in video_prompt_type_value , height = gallery_height, value= ui_defaults.get("video_mask", None)) 
 
                 mask_expand = gr.Slider(-10, 50, value=ui_defaults.get("mask_expand", 0), step=1, label="Expand / Shrink Mask Area", visible= "V" in video_prompt_type_value and "A" in video_prompt_type_value and not "U" in video_prompt_type_value )
@@ -7827,7 +7865,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                                     ("Generate always a 13 Frames long Video (x2.5 slower)",1013),
                                     ("Generate always a 17 Frames long Video (x3.0 slower)",1017),
                                 ],
-                                value=ui_defaults.get("min_frames_if_references",5 if vace else 1),
+                                value=ui_defaults.get("min_frames_if_references",9 if vace else 1),
                                 visible=True,
                                 scale = 1,
                                 label="Generate more frames to preserve Reference Image Identity / Control Image Information or improve"
@@ -7953,7 +7991,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 output_trigger = gr.Text(interactive= False, visible=False)
                 refresh_form_trigger = gr.Text(interactive= False, visible=False)
                 fill_wizard_prompt_trigger = gr.Text(interactive= False, visible=False)
-                saveform_trigger = gr.Text(interactive= False, visible=False)
+                save_form_trigger = gr.Text(interactive= False, visible=False)
 
             with gr.Accordion("Video Info and Late Post Processing & Audio Remuxing", open=False) as video_info_accordion:
                 with gr.Tabs() as video_info_tabs:
@@ -7970,7 +8008,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                             video_info_to_start_image_btn = gr.Button("To Start Image", size ="sm", min_width= 1, visible = any_start_image )
                             video_info_to_end_image_btn = gr.Button("To End Image", size ="sm", min_width= 1, visible = any_end_image)
                             video_info_to_image_guide_btn = gr.Button("To Control Image", min_width= 1, size ="sm", visible = any_control_image )
-                            video_info_to_image_mask_btn = gr.Button("To Mask Image", min_width= 1, size ="sm", visible = any_image_mask)
+                            video_info_to_image_mask_btn = gr.Button("To Mask Image", min_width= 1, size ="sm", visible = any_image_mask and False)
                             video_info_to_reference_image_btn = gr.Button("To Reference Image", min_width= 1, size ="sm", visible = any_reference_image)
                             video_info_eject_image_btn = gr.Button("Eject Image", min_width= 1, size ="sm")
                     with gr.Tab("Post Processing", id= "post_processing", visible = True) as video_postprocessing_tab:
@@ -8080,9 +8118,9 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
             image_prompt_type_endcheckbox.change(fn=refresh_image_prompt_type_endcheckbox, inputs=[state, image_prompt_type, image_prompt_type_radio, image_prompt_type_endcheckbox], outputs=[image_prompt_type, image_end_row] ) 
             # video_prompt_video_guide_trigger.change(fn=refresh_video_prompt_video_guide_trigger, inputs=[state, video_prompt_type, video_prompt_video_guide_trigger], outputs=[video_prompt_type, video_prompt_type_video_guide, video_guide, keep_frames_video_guide, denoising_strength, video_guide_outpainting_col, video_prompt_type_video_mask, video_mask, mask_expand])
             video_prompt_type_image_refs.input(fn=refresh_video_prompt_type_image_refs, inputs = [state, video_prompt_type, video_prompt_type_image_refs], outputs = [video_prompt_type, image_refs_row, remove_background_images_ref,  image_refs_relative_size, frames_positions,video_guide_outpainting_col], show_progress="hidden")
-            video_prompt_type_video_guide.input(fn=refresh_video_prompt_type_video_guide, inputs = [state, video_prompt_type, video_prompt_type_video_guide, image_mode], outputs = [video_prompt_type, video_guide, image_guide, keep_frames_video_guide, denoising_strength, video_guide_outpainting_col, video_prompt_type_video_mask, video_mask, image_mask, mask_expand], show_progress="hidden")
-            video_prompt_type_video_guide_alt.input(fn=refresh_video_prompt_type_video_guide_alt, inputs = [state, video_prompt_type, video_prompt_type_video_guide_alt], outputs = [video_prompt_type, video_guide, image_refs_row, denoising_strength ], show_progress="hidden")
-            video_prompt_type_video_mask.input(fn=refresh_video_prompt_type_video_mask, inputs = [state, video_prompt_type, video_prompt_type_video_mask, image_mode], outputs = [video_prompt_type, video_mask, image_mask, mask_expand], show_progress="hidden")
+            video_prompt_type_video_guide.input(fn=refresh_video_prompt_type_video_guide, inputs = [state, video_prompt_type, video_prompt_type_video_guide, image_mode, image_mask_guide, image_guide, image_mask], outputs = [video_prompt_type, video_guide, image_guide, keep_frames_video_guide, denoising_strength, video_guide_outpainting_col, video_prompt_type_video_mask, video_mask, image_mask, image_mask_guide, mask_expand], show_progress="hidden") 
+            video_prompt_type_video_guide_alt.input(fn=refresh_video_prompt_type_video_guide_alt, inputs = [state, video_prompt_type, video_prompt_type_video_guide_alt, image_mode], outputs = [video_prompt_type, video_guide, image_guide, image_refs_row, denoising_strength ], show_progress="hidden")
+            video_prompt_type_video_mask.input(fn=refresh_video_prompt_type_video_mask, inputs = [state, video_prompt_type, video_prompt_type_video_mask, image_mode, image_mask_guide, image_guide, image_mask], outputs = [video_prompt_type, video_mask, image_mask_guide, image_guide, image_mask, mask_expand], show_progress="hidden")
             video_prompt_type_alignment.input(fn=refresh_video_prompt_type_alignment, inputs = [state, video_prompt_type, video_prompt_type_alignment], outputs = [video_prompt_type])
             multi_prompts_gen_type.select(fn=refresh_prompt_labels, inputs=[multi_prompts_gen_type, image_mode], outputs=[prompt, wizard_prompt, image_end], show_progress="hidden")
             video_guide_outpainting_top.input(fn=update_video_guide_outpainting, inputs=[video_guide_outpainting, video_guide_outpainting_top, gr.State(0)], outputs = [video_guide_outpainting], trigger_mode="multiple" )
@@ -8120,7 +8158,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 gen["status_display"] = True
                 return time.time()
 
-            start_quit_timer_js, cancel_quit_timer_js, trigger_zip_download_js, trigger_settings_download_js = get_js()
+            start_quit_timer_js, cancel_quit_timer_js, trigger_zip_download_js, trigger_settings_download_js, click_brush_js = get_js()
 
             status_trigger.change(refresh_status_async, inputs= [state] , outputs= [gen_status], show_progress_on= [gen_status])
 
@@ -8161,7 +8199,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 outputs= None
             ).then( fn=enhance_prompt, inputs =[state, prompt, prompt_enhancer, multi_images_gen_type, override_profile ] , outputs= [prompt, wizard_prompt])
 
-            saveform_trigger.change(fn=validate_wizard_prompt,
+            save_form_trigger.change(fn=validate_wizard_prompt,
                 inputs= [state, wizard_prompt_activated_var, wizard_variables_var,  prompt, wizard_prompt, *prompt_vars] ,
                 outputs= [prompt],
                 show_progress="hidden",
@@ -8170,7 +8208,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 outputs= None
             )
 
-            main_tabs.select(fn=detect_auto_save_form, inputs= [state], outputs= saveform_trigger, trigger_mode="multiple")
+            main_tabs.select(fn=detect_auto_save_form, inputs= [state], outputs= save_form_trigger, trigger_mode="multiple")
 
 
             video_info_add_videos_btn.click(fn=add_videos_to_gallery, inputs =[state, output, last_choice, files_to_load], outputs = [output, files_to_load, video_info_tabs] )
@@ -8179,7 +8217,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
             video_info_to_video_source_btn.click(fn=video_to_source_video, inputs =[state, output, last_choice], outputs = [video_source] )
             video_info_to_start_image_btn.click(fn=image_to_ref_image_add, inputs =[state, output, last_choice, image_start, gr.State("Start Image")], outputs = [image_start] )
             video_info_to_end_image_btn.click(fn=image_to_ref_image_add, inputs =[state, output, last_choice, image_end, gr.State("End Image")], outputs = [image_end] )
-            video_info_to_image_guide_btn.click(fn=image_to_ref_image_guide, inputs =[state, output, last_choice], outputs = [image_guide, image_mask_guide] )
+            video_info_to_image_guide_btn.click(fn=image_to_ref_image_guide, inputs =[state, output, last_choice], outputs = [image_guide, image_mask_guide]).then(fn=None, inputs=[], outputs=[], js=click_brush_js )
             video_info_to_image_mask_btn.click(fn=image_to_ref_image_set, inputs =[state, output, last_choice, image_mask, gr.State("Image Mask")], outputs = [image_mask] )
             video_info_to_reference_image_btn.click(fn=image_to_ref_image_add, inputs =[state, output, last_choice, image_refs, gr.State("Ref Image")],  outputs = [image_refs] )
             video_info_postprocessing_btn.click(fn=apply_post_processing, inputs =[state, output, last_choice, PP_temporal_upsampling, PP_spatial_upsampling, PP_film_grain_intensity, PP_film_grain_saturation], outputs = [mode, generate_trigger, add_to_queue_trigger ] )
@@ -8430,7 +8468,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
                 outputs=[modal_container]
             )
 
-    return ( state, loras_choices, lset_name, resolution, refresh_form_trigger,
+    return ( state, loras_choices, lset_name, resolution, refresh_form_trigger, save_form_trigger,
             #  video_guide, image_guide, video_mask, image_mask, image_refs,   
             ) 
  
@@ -8926,7 +8964,12 @@ def set_new_tab(tab_state, new_tab_no):
     return gr.Tabs() 
 
 def select_tab(tab_state, evt:gr.SelectData):
-    return set_new_tab(tab_state, evt.index)
+    old_tab_no = tab_state.get("tab_no",0)
+    if old_tab_no == 0:
+        saveform_trigger = get_unique_id()
+    else:
+        saveform_trigger = gr.update()
+    return set_new_tab(tab_state, evt.index), saveform_trigger
 
 def get_js():
     start_quit_timer_js = """
@@ -9029,7 +9072,21 @@ def get_js():
         }
     }
     """
-    return start_quit_timer_js, cancel_quit_timer_js, trigger_zip_download_js, trigger_settings_download_js
+
+    click_brush_js = """
+    () => {
+        setTimeout(() => {
+            const brushButton = document.querySelector('button[aria-label="Brush"]');
+            if (brushButton) {
+                brushButton.click();
+                console.log('Brush button clicked');
+            } else {
+                console.log('Brush button not found');
+            }
+        }, 1000);
+    }    """
+
+    return start_quit_timer_js, cancel_quit_timer_js, trigger_zip_download_js, trigger_settings_download_js, click_brush_js
 
 def create_ui():
     global vmc_event_handler    
@@ -9401,7 +9458,7 @@ def create_ui():
                         stats_element = stats_app.get_gradio_element()
 
                 with gr.Row():
-                    (   state, loras_choices, lset_name, resolution, refresh_form_trigger
+                    (   state, loras_choices, lset_name, resolution, refresh_form_trigger, save_form_trigger
                         # video_guide, image_guide, video_mask, image_mask, image_refs, 
                     ) = generate_video_tab(model_family=model_family, model_choice=model_choice, header=header, main = main, main_tabs =main_tabs)
             with gr.Tab("Guides", id="info") as info_tab:
@@ -9417,7 +9474,7 @@ def create_ui():
                 generate_about_tab()
         if stats_app is not None:
             stats_app.setup_events(main, state)
-        main_tabs.select(fn=select_tab, inputs= [tab_state], outputs= main_tabs, trigger_mode="multiple")
+        main_tabs.select(fn=select_tab, inputs= [tab_state], outputs= [main_tabs, save_form_trigger], trigger_mode="multiple")
         return main
 
 if __name__ == "__main__":