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==4.44.1")
 
 import gradio as gr
 from loguru import logger
@@ -103,6 +103,8 @@ from kosmos_utils import *
 
 from util_tencent import getTextTrans
 
+huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
+
 config_file = 'GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py'
 ckpt_repo_id = "ShilongLiu/GroundingDINO"
 ckpt_filenmae = "groundingdino_swint_ogc.pth"
@@ -587,7 +589,7 @@ def get_time_cost(run_task_time, time_cost_str):
     run_task_time = now_time
     return run_task_time, time_cost_str
 
-def load_kolors_inpainting(inpaint_prompt, input_image, mask_image):
+def processs_inpainting(inpaint_prompt, input_image, mask_image, image_input_composite, debug=False):
     from gradio_client import Client, handle_file
     import tempfile
     MAX_IMAGE_SIZE = 1024
@@ -602,8 +604,8 @@ def load_kolors_inpainting(inpaint_prompt, input_image, mask_image):
         return image
 
     try:
-        # logger.info(f'load_kolors_inpainting_input_image={inpaint_prompt} // {input_image}')
-        # logger.info(f'load_kolors_inpainting_mask_image={mask_image}')
+        # 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
@@ -623,7 +625,7 @@ def load_kolors_inpainting(inpaint_prompt, input_image, mask_image):
             _, 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'load_kolors_inpainting_temp_file_background_={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:
@@ -634,29 +636,57 @@ def load_kolors_inpainting(inpaint_prompt, input_image, mask_image):
             # 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'load_kolors_inpainting_temp_file___mask_={temp_file_path}')
+            # logger.info(f'processs_inpainting_temp_file___mask_={temp_file_path}')
             job_image["layers"] = [handle_file(temp_file_path)]            
 
-        # logger.info(f'load_kolors_inpainting_job_image={job_image}')
-        # logger.info(f'load_kolors_inpainting_job_mask_image={job_mask_image}')
-
-        client = Client("Kwai-Kolors/Kolors-Inpainting")        
-        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 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_job_image={job_image}')
+        logger.info(f'processs_inpainting_job_mask_image={job_mask_image}')
+
+        if 0==0:
+            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:
+            client = Client("ameerazam08/FLUX.1-dev-Inpainting-Model-Beta-GPU")
+            job = client.submit(
+                    input_image_editor=job_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="",
+                    controlnet_conditioning_scale=0.9,
+                    guidance_scale=3.5,
+                    seed=124,
+                    num_inference_steps=24,
+                    true_guidance_scale=3.5,
+                    api_name="/process"
+            )
+        
+        debug = True
+        if debug:
+            count = 0
+            logger.info(f'{count}___{job.status()}')
         while not job.done():
+            if debug:
+                count += 1
+                logger.info(f'{count}___{job.status()}')
             time.sleep(0.1)
-
+        
         result = job.outputs()
-        logger.info(f'load_kolors_inpainting_result={result}')
+        logger.info(f'processs_inpainting_result={result}')
         if len(result) <= 0:
             return None
 
@@ -668,7 +698,7 @@ def load_kolors_inpainting(inpaint_prompt, input_image, mask_image):
             background.paste(im, mask=im.split()[3]) 
         return im 
     except Exception as e:
-        logger.info(f'load_kolors_inpainting_[Error]:' + str(e))
+        logger.info(f'processs_inpainting_[Error]:' + str(e))
         return None
 
 def run_anything_task(input_image, text_prompt, task_type, inpaint_prompt, box_threshold, text_threshold, 
@@ -682,12 +712,15 @@ def run_anything_task(input_image, text_prompt, task_type, inpaint_prompt, box_t
         
     # logger.info(f"input_image==={input_image}")
     ori_input_image = input_image
+    image_input_composite = None
     if 'background' in input_image.keys():
         input_image['image'] = input_image['background'].convert("RGB")
         if len(input_image['layers']) > 0:
             img_arr = np.array(input_image['layers'][0].convert("L"))
             img_arr = np.where(img_arr > 0, 1, img_arr)
             input_image['mask'] = Image.fromarray(255*img_arr.astype('uint8'))
+        if 'composite' in input_image.keys():
+            image_input_composite = input_image['composite']
 
     if (task_type == 'Kosmos-2'):
         global kosmos_model, kosmos_processor
@@ -865,10 +898,10 @@ def run_anything_task(input_image, text_prompt, task_type, inpaint_prompt, box_t
                 run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
             
             # image_inpainting = sd_model(prompt=inpaint_prompt, image=image_source_for_inpaint, mask_image=image_mask_for_inpaint).images[0]
-            image_inpainting = load_kolors_inpainting(inpaint_prompt, input_image, image_mask_for_inpaint)
+            image_inpainting = processs_inpainting(inpaint_prompt, input_image, image_mask_for_inpaint, image_input_composite)
             if image_inpainting is None:
-                logger.info(f'load_kolors_inpainting_failed_')
-                time_cost_str = f"load_kolors_inpainting_task__failed!"
+                logger.info(f'processs_inpainting_failed_')
+                time_cost_str = f"processs_inpainting_task__failed!"
                 return None, None, time_cost_str, gr.update(visible=(time_cost_str !='')), None, None, None
         else:
             # remove from mask
@@ -979,7 +1012,7 @@ def get_model_device(module):
 def main_gradio(args):
     block = gr.Blocks(
             title="SAM and others",
-            theme="shivi/calm_seafoam@>=0.0.1,<1.0.0",
+            # theme="shivi/calm_seafoam@>=0.0.1,<1.0.0",
         )
     with block:
         with gr.Row():
@@ -999,8 +1032,13 @@ def main_gradio(args):
                 
                 brush_color = "#00FF00"
                 color_mode = "fixed"
-                input_image = gr.ImageMask(sources=["upload", "webcam"], image_mode='RGB', elem_id="image_upload", type='pil', label="Upload",
-                                   brush=gr.Brush(colors=[brush_color], color_mode=color_mode))
+                input_image = gr.ImageEditor(sources=["upload", "webcam"], 
+                                           image_mode='RGB', 
+                                           elem_id="image_upload", 
+                                           type='pil', 
+                                           label="Upload",
+                                           layers=False,
+                                           brush=gr.Brush(colors=[brush_color], color_mode=color_mode))
                 
                 task_type = gr.Radio(task_types,  value="detection", 
                                                 label='Task type', visible=True) 

requirements.txt

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