update app.py

app.py

@@ -4,7 +4,7 @@ warnings.filterwarnings('ignore')
 
 import subprocess, io, os, sys, time
 
-os.system("pip install gradio==4.42.0")
+# os.system("pip install gradio==4.42.0")
 
 import gradio as gr
 from loguru import logger
@@ -607,65 +607,68 @@ def processs_inpainting(inpaint_prompt, input_image, mask_image, image_input_com
         # logger.info(f'processs_inpainting_input_image={inpaint_prompt} // {input_image}')
         # logger.info(f'processs_inpainting_mask_image={mask_image}')
 
-        job_image = {}
-        job_mask_image = None
-        if 'background' in input_image.keys():
-            width, height = input_image['background'].size
-            if max(width, height) > MAX_IMAGE_SIZE:
-                if width > height:
-                    resize_width = MAX_IMAGE_SIZE
-                    resize_height = int(height * MAX_IMAGE_SIZE / width)
-                else:
-                    resize_height = MAX_IMAGE_SIZE
-                    resize_width = int(width * MAX_IMAGE_SIZE / height)
-            else:
-                resize_width, resize_height = width, height
-            
-            logger.info(f"resize____{width}, {height}==>{resize_width}, {resize_height}")
-            _, temp_file_path = tempfile.mkstemp(suffix='.png')
-            img = input_image['background'].convert("RGB").resize((resize_width, resize_height))
-            img.save(temp_file_path)
-            # logger.info(f'processs_inpainting_temp_file_background_={temp_file_path}')
-            job_image["background"] = handle_file(temp_file_path)
-
-        if mask_image is not None:
-            _, temp_file_path = tempfile.mkstemp(suffix='.png')
-            img = mask_image.convert("RGB").resize((resize_width, resize_height))
-            # RGB(0,0,0) -->  RGB(230,230,230)           
-            img = change_RGB_value(img, 0, 0, 0, 230, 230, 230)
-            # RGB(255,255,255) --> RGB(170,170,170)
-            img = change_RGB_value(img, 255, 255, 255, 170, 170, 170)
-            img.save(temp_file_path)
-            # logger.info(f'processs_inpainting_temp_file___mask_={temp_file_path}')
-            job_image["layers"] = [handle_file(temp_file_path)]            
-
-        if image_input_composite:
-            _, temp_file_path = tempfile.mkstemp(suffix='.png')
-            image_input_composite.save(temp_file_path)
-            job_image["composite"] = handle_file(temp_file_path)
+        # job_image = {}
+        # job_mask_image = None
+        # if 'background' in input_image.keys():
+        #     width, height = input_image['background'].size
+        #     if max(width, height) > MAX_IMAGE_SIZE:
+        #         if width > height:
+        #             resize_width = MAX_IMAGE_SIZE
+        #             resize_height = int(height * MAX_IMAGE_SIZE / width)
+        #         else:
+        #             resize_height = MAX_IMAGE_SIZE
+        #             resize_width = int(width * MAX_IMAGE_SIZE / height)
+        #     else:
+        #         resize_width, resize_height = width, height
             
-        logger.info(f'processs_inpainting_job_image={job_image}')
-        logger.info(f'processs_inpainting_job_mask_image={job_mask_image}')
-
-        if 0==1:
-            logger.info(f'processs_inpainting_HF = Kwai-Kolors/Kolors-Inpainting')
-            client = Client("Kwai-Kolors/Kolors-Inpainting", hf_token=huggingface_token, verbose=True)        
-            job = client.submit(
-                    prompt=inpaint_prompt,
-                    image=job_image,
-                    mask_image=job_mask_image,
-                    negative_prompt="broken fingers, deformed fingers, deformed hands, stumps, blurriness, low quality",
-                    seed=0,
-                    randomize_seed=True,
-                    guidance_scale=6.0,
-                    num_inference_steps=25,
-                    api_name="/infer"
-            )
-        elif 0==0:
+        #     logger.info(f"resize____{width}, {height}==>{resize_width}, {resize_height}")
+        #     _, temp_file_path = tempfile.mkstemp(suffix='.png')
+        #     img = input_image['background'].convert("RGB").resize((resize_width, resize_height))
+        #     img.save(temp_file_path)
+        #     # logger.info(f'processs_inpainting_temp_file_background_={temp_file_path}')
+        #     job_image["background"] = handle_file(temp_file_path)
+
+        # if mask_image is not None:
+        #     _, temp_file_path = tempfile.mkstemp(suffix='.png')
+        #     logger.info(f"mask_temp_file_path={temp_file_path}")
+        #     img = mask_image.convert("RGB").resize((resize_width, resize_height))
+        #     # RGB(0,0,0) -->  RGB(230,230,230)           
+        #     img = change_RGB_value(img, 0, 0, 0, 230, 230, 230)
+        #     # RGB(255,255,255) --> RGB(170,170,170)
+        #     # img = change_RGB_value(img, 255, 255, 255, 170, 170, 170)
+        #     img.save(temp_file_path)
+        #     # logger.info(f'processs_inpainting_temp_file___mask_={temp_file_path}')
+        #     job_image["layers"] = [handle_file(temp_file_path)]            
+
+        # if image_input_composite:
+        #     _, temp_file_path = tempfile.mkstemp(suffix='.png')
+        #     image_input_composite.save(temp_file_path)
+        #     job_image["composite"] = handle_file(temp_file_path)
+
+        # logger.info(f'processs_inpainting_input_image={job_image}')    
+        # logger.info(f'processs_inpainting_job_image={job_image}')
+        # logger.info(f'processs_inpainting_job_mask_image={job_mask_image}')
+
+        # if 0==1:
+        #     logger.info(f'processs_inpainting_HF = Kwai-Kolors/Kolors-Inpainting')
+        #     client = Client("Kwai-Kolors/Kolors-Inpainting", hf_token=huggingface_token, verbose=True)        
+        #     job = client.submit(
+        #             prompt=inpaint_prompt,
+        #             image=job_image,
+        #             mask_image=job_mask_image,
+        #             negative_prompt="broken fingers, deformed fingers, deformed hands, stumps, blurriness, low quality",
+        #             seed=0,
+        #             randomize_seed=True,
+        #             guidance_scale=6.0,
+        #             num_inference_steps=25,
+        #             api_name="/infer"
+        #     )
+        
+        if 0==0:
             logger.info(f'processs_inpainting_HF = ameerazam08/FLUX.1-dev-Inpainting-Model-Beta-GPU')
             client = Client("ameerazam08/FLUX.1-dev-Inpainting-Model-Beta-GPU")
             job = client.submit(
-                    input_image_editor=job_image,
+                    input_image_editor=input_image,
                     # input_image_editor={"background":handle_file('https://ameerazam08-flux-1-dev-inpainting-model-beta-gpu.hf.space/file=/tmp/gradio/d9270300d40346834ccf596c97d9795fef6af692/background.png'),"layers":[handle_file('https://ameerazam08-flux-1-dev-inpainting-model-beta-gpu.hf.space/file=/tmp/gradio/4245eafd2d9aa8969d94dc22ffff62be95d4df02/layer_0.png')],"composite":handle_file('https://ameerazam08-flux-1-dev-inpainting-model-beta-gpu.hf.space/file=/tmp/gradio/7fe6ddfacbb3b394d19a32b01113a0460e2279ac/composite.png')},
                     prompt=inpaint_prompt,
                     negative_prompt="",
@@ -1031,7 +1034,7 @@ def main_gradio(args):
                 if kosmos_enable:
                     task_types.append("Kosmos-2")           
                 
-                brush_color = "#00FF00"
+                brush_color = "#FFFFFF"
                 color_mode = "fixed"
                 input_image = gr.ImageEditor(sources=["upload", "webcam"], 
                                            image_mode='RGB', 

requirements.txt

@@ -1,7 +1,7 @@
 accelerate
 addict
 diffusers
-# gradio==3.36.1
+gradio==4.42.0
 huggingface_hub
 matplotlib