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gradio_demo/app.py

@@ -30,7 +30,6 @@ from pipeline_stable_diffusion_xl_instantid_full import StableDiffusionXLInstant
 from model_util import load_models_xl, get_torch_device, torch_gc
 
 import os
-import requests
 
 # try:
 #     # Send a GET request to the URL
@@ -75,21 +74,11 @@ logo = logo.resize((100, 100))
 from cv2 import imencode
 import base64
 
-# def encode_pil_to_base64_new(pil_image):
-#     print("AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA")
-#     image_arr = np.asarray(pil_image)[:,:,::-1]
-#     _, byte_data = imencode('.png', image_arr)        
-#     base64_data = base64.b64encode(byte_data)
-#     base64_string_opencv = base64_data.decode("utf-8")
-#     return "data:image/png;base64," + base64_string_opencv
-
 import gradio as gr
 from google.cloud import storage
 from io import BytesIO
 
 
-# gr.processing_utils.encode_pil_to_base64 = encode_pil_to_base64_new
-
 def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=False):
 
     if pretrained_model_name_or_path.endswith(
@@ -136,16 +125,8 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
     pipe.disable_lora()
     
     def remove_tips():
-        print("GG")
         return gr.update(visible=False)
 
-    
-    # prompts = [
-    #     ["superman","Vibrant Color"], ["japanese anime character with white/neon hair","Watercolor"], 
-    #     # ["Suited professional","(No style)"], 
-    #     ["Scooba diver","Line art"], ["eskimo","Snow"]
-    # ]
-
     def convert_from_cv2_to_image(img: np.ndarray) -> Image:
         return Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
 
@@ -170,28 +151,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         # if email != "":
         p,n = styles.get(style, styles.get(STYLE_NAMES[1]))
         return generate_image(face_file, p[3], n)
-    
-#     def validate_and_process(face_file, style, email):
-    
-#     # Your processing logic here
-#     gallery1, gallery2, gallery3, gallery4 = run_for_prompts1(face_file, style), run_for_prompts2(face_file, style), run_for_prompts3(face_file, style), run_for_prompts4(face_file, style)
-#     return gallery1, gallery2, gallery3, gallery4
-    
-#     def upload_image_to_gcs(source_file_name, destination_blob_name):
-#         bucket_name="idfy-gff-public"
-#         # Initialize a GCP client
-#         storage_client = storage.Client()
-
-#         # Get the bucket
-#         bucket = storage_client.get_bucket(bucket_name)
-
-#         # Create a blob object from the filename
-#         blob = bucket.blob(destination_blob_name)
-
-#         # Upload the file to GCS
-#         blob.upload_from_filename(source_file_name)
-
-#         print(f"File {source_file_name} uploaded to {destination_blob_name}.")
         
     def upload_pil_image_to_gcs(image, destination_blob_name):
         bucket_name="idfy-gff-public"
@@ -212,8 +171,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         # Upload the image to GCS
         blob.upload_from_file(image_byte_array, content_type=f'image/png')
 
-        print(f"Image uploaded to {destination_blob_name} in bucket {bucket_name}.")
-
     def draw_kps(image_pil, kps, color_list=[(255,0,0), (0,255,0), (0,0,255), (255,255,0), (255,0,255)]):
         stickwidth = 4
         limbSeq = np.array([[0, 2], [1, 2], [3, 2], [4, 2]])
@@ -246,7 +203,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
                 pad_to_max_side=True, mode=PIL.Image.BILINEAR, base_pixel_number=64):
 
             w, h = input_image.size
-            print(f"Original Size --> {input_image.size}")
             if size is not None:
                 w_resize_new, h_resize_new = size
             else:
@@ -264,15 +220,13 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
                 offset_y = (max_side - h_resize_new) // 2
                 res[offset_y:offset_y+h_resize_new, offset_x:offset_x+w_resize_new] = np.array(input_image)
                 input_image = Image.fromarray(res)
-            
-            print(f"Final modified image size --> {input_image.size}")
             return input_image
 
     # def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
     #     p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
     #     return p.replace("{prompt}", positive), n + ' ' + negative
     
-    def store_images(email, gallery1, gallery2, gallery3, gallery4,consent):
+    def store_images(email, gallery1, gallery2, gallery3, gallery4,consent,style):
         if not email:
             raise gr.Error("Email Id not provided")
         if not consent:
@@ -280,8 +234,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         for i, img in enumerate([gallery1, gallery2, gallery3, gallery4], start=1):
             if isinstance(img, np.ndarray):
                 img = Image.fromarray(img)
-            print(f"Gallery {i} type after conversion: {type(img)}")
-            dest = f'{email}/img{i}.png'
+            dest = f'{email}/img{i}@{style}.png'
             upload_pil_image_to_gcs(img,dest) 
         gr.Info("Thankyou!! Your avatar is on the way to your inbox")
         return None,None,None,None,None
@@ -337,10 +290,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         num_steps = 15
         guidance_scale = 5
         seed = random.randint(0, MAX_SEED)
-        print(f"Seed --> {seed}")
-        
-        # negative_prompt = ""
-        # negative_prompt += neg
         enhance_face_region = True
         if enable_LCM:
             pipe.enable_lora()
@@ -351,14 +300,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
     
         if face_image is None:
             raise gr.Error(f"Cannot find any input face image! Please upload the face image")
-        
-        # if prompt is None:
-        #     prompt = "a person"
-        
-        # apply the style template
-        # prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
-        
-        # face_image = load_image(face_image_path)
         face_image = resize_img(face_image)
         face_image_cv2 = convert_from_image_to_cv2(face_image)
         height, width, _ = face_image_cv2.shape
@@ -399,9 +340,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
                         
         generator = torch.Generator(device=device).manual_seed(seed)
         
-        print("Start inference...")
-        print(f"[Debug] Prompt: {prompt}, \n[Debug] Neg Prompt: {negative_prompt}")
-        
         pipe.set_ip_adapter_scale(adapter_strength_ratio)
         images = pipe(
             prompt=prompt,
@@ -434,21 +372,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
     article = r""""""
 
     tips = r""""""
-    # css = '''
-    # .gradio-container {
-    #     width: 95% !important; 
-    #     background-image: url('./InstantID/gradio_demo/logo.png'); 
-    #     background-size: cover;
-    #     background-position: center;
-    # } 
-    # .image-gallery {
-    #     height: 100vh !important; 
-    #     overflow: auto;
-    # }
-    # .gradio-row .gradio-element { 
-    #     margin: 0 !important; 
-    # }
-    # '''
     css = '''
     .gradio-container {width: 100% !important; color: white; background: linear-gradient(135deg, #1C43B9, #254977, #343434);} 
     .gradio-row .gradio-element { margin: 0 !important; }
@@ -477,38 +400,14 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
             submit = gr.Button("Submit", variant="primary",elem_id="submit-btn")
             with gr.Column():
                 with gr.Row():
-                    gallery1 = gr.Image(label="Generated Images", interactive=False)
-                    gallery2 = gr.Image(label="Generated Images", interactive=False)
+                    gallery1 = gr.Image(label="Generated Images", interactive=False, height=640, width=640)
+                    gallery2 = gr.Image(label="Generated Images", interactive=False, height=640, width=640)
                 with gr.Row():
-                    gallery3 = gr.Image(label="Generated Images", interactive=False)
-                    gallery4 = gr.Image(label="Generated Images", interactive=False)
+                    gallery3 = gr.Image(label="Generated Images", interactive=False, height=640, width=640)
+                    gallery4 = gr.Image(label="Generated Images", interactive=False, height=640, width=640)
             email = gr.Textbox(label="Email", info="Enter your email address", value="")
             consent = gr.Checkbox(label="I am giving my consent to use my data to share my AI Avtar and IDfy relevant information from time to time", value=True)
             submit1 = gr.Button("SUBMIT", variant = "primary", elem_id="store-btn")
-#     with gr.Blocks(css=css) as demo:
-
-#         # description
-#         gr.Markdown(title)
-#         with gr.Column():
-#             with gr.Row():
-#                 gr.Image("./gradio_demo/logo.png",scale=0,min_width=50,show_label=False,show_download_button=False)
-#                 gr.Markdown(description)
-#             style = gr.Dropdown(label="Choose your STYLE", choices=STYLE_NAMES)
-#             face_file = gr.Image(label="Upload a photo of your face", type="pil",sources="webcam", height=400, width=500)
-#             submit = gr.Button("Submit", variant="primary")
-#             with gr.Column():
-#                 with gr.Row():
-#                     gallery1 = gr.Image(label="Generated Images")
-#                     gallery2 = gr.Image(label="Generated Images")
-#                 with gr.Row():
-#                     gallery3 = gr.Image(label="Generated Images")
-#                     gallery4 = gr.Image(label="Generated Images")
-#             email = gr.Textbox(label="Email",
-#                     info="Enter your email address",
-#                     value="")
-#             consent = gr.Checkbox(label="I am giving my consent to use my data to share my AI Avtar and IDfy relevant information from time to time")
-#             submit1 = gr.Button("STORE", variant="primary")
-#                 # submit1 = gr.Button("Store")
             usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips ,visible=False)
                 
             face_file.upload(
@@ -534,33 +433,33 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
                 inputs=[face_file,style],
                 outputs=[gallery4]
             )
-            # submit.click(
-            #     fn=remove_tips,
-            #     outputs=usage_tips,
-            #     queue=True,
-            #     api_name=False,
-            #     show_progress = "full"
-            # ).then(
-            #     fn=run_for_prompts1,
-            #     inputs=[face_file,style],
-            #     outputs=[gallery1]
-            # ).then(
-            #     fn=run_for_prompts2,
-            #     inputs=[face_file,style],
-            #     outputs=[gallery2]
-            # ).then(
-            #     fn=run_for_prompts3,
-            #     inputs=[face_file,style],
-            #     outputs=[gallery3]
-            # ).then(
-            #     fn=run_for_prompts4,
-            #     inputs=[face_file,style],
-            #     outputs=[gallery4]
-            # )
+            submit.click(
+                fn=remove_tips,
+                outputs=usage_tips,
+                queue=True,
+                api_name=False,
+                show_progress = "full"
+            ).then(
+                fn=run_for_prompts1,
+                inputs=[face_file,style],
+                outputs=[gallery1]
+            ).then(
+                fn=run_for_prompts2,
+                inputs=[face_file,style],
+                outputs=[gallery2]
+            ).then(
+                fn=run_for_prompts3,
+                inputs=[face_file,style],
+                outputs=[gallery3]
+            ).then(
+                fn=run_for_prompts4,
+                inputs=[face_file,style],
+                outputs=[gallery4]
+            )
             
             submit1.click(
                 fn=store_images,
-                inputs=[email,gallery1,gallery2,gallery3,gallery4,consent],
+                inputs=[email,gallery1,gallery2,gallery3,gallery4,consent,style],
                 outputs=[face_file,gallery1,gallery2,gallery3,gallery4])
             
         
@@ -568,119 +467,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         gr.Markdown(article)
 
     demo.launch(share=True)
-
-#     with gr.Blocks(css=css, js=js) as demo:
-
-#         # description
-#         gr.Markdown(title)
-#         with gr.Row():
-#             gr.Image("./gradio_demo/logo.png",scale=0,min_width=50,show_label=False,show_download_button=False)
-#             gr.Markdown(description)
-#         with gr.Row():
-#             with gr.Column():
-#                 style = gr.Dropdown(label="Choose your STYLE", choices=STYLE_NAMES)
-#                 face_file = gr.Image(label="Upload a photo of your face", type="pil",sources="webcam")
-#                 submit = gr.Button("Submit", variant="primary")
-#             with gr.Column():
-#                 with gr.Row():
-#                     gallery1 = gr.Image(label="Generated Images")
-#                     gallery2 = gr.Image(label="Generated Images")
-#                 with gr.Row():
-#                     gallery3 = gr.Image(label="Generated Images")
-#                     gallery4 = gr.Image(label="Generated Images")
-#                 email = gr.Textbox(label="Email",
-#                         info="Enter your email address",
-#                         value="")
-            
-#             usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips ,visible=False)
-#             # identitynet_strength_ratio = gr.Slider(
-#             #     label="IdentityNet strength (for fidelity)",
-#             #     minimum=0,
-#             #     maximum=1.5,
-#             #     step=0.05,
-#             #     value=0.95,
-#             # )
-#             # adapter_strength_ratio = gr.Slider(
-#             #     label="Image adapter strength (for detail)",
-#             #     minimum=0,
-#             #     maximum=1.5,
-#             #     step=0.05,
-#             #     value=0.60,
-#             # )
-#             # negative_prompt = gr.Textbox(
-#             #     label="Negative Prompt", 
-#             #     placeholder="low quality",
-#             #     value="(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
-#             # )
-#             # num_steps = gr.Slider( 
-#             #     label="Number of sample steps",
-#             #     minimum=15,
-#             #     maximum=100,
-#             #     step=1,
-#             #     value=5 if enable_lcm_arg else 15,
-#             # )
-#             # guidance_scale = gr.Slider(
-#             #     label="Guidance scale",
-#             #     minimum=0.1,
-#             #     maximum=10.0,
-#             #     step=0.1,
-#             #     value=0 if enable_lcm_arg else 8.5,
-#             # )
-#             # if email is None:
-#             #     print("STOPPPP")
-#             #     raise gr.Error("Email ID is compulsory")
-#             face_file.upload(
-#                 fn=remove_tips,
-#                 outputs=usage_tips,
-#                 queue=True,
-#                 api_name=False,
-#                 show_progress = "full"
-#             ).then(
-#                 fn=run_for_prompts1,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery1]
-#             ).then(
-#                 fn=run_for_prompts2,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery2]
-#             ).then(
-#                 fn=run_for_prompts3,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery3]
-#             ).then(
-#                 fn=run_for_prompts4,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery4]
-#             )
-#             submit.click(
-#                 fn=remove_tips,
-#                 outputs=usage_tips,
-#                 queue=True,
-#                 api_name=False,
-#                 show_progress = "full"
-#             ).then(
-#                 fn=run_for_prompts1,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery1]
-#             ).then(
-#                 fn=run_for_prompts2,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery2]
-#             ).then(
-#                 fn=run_for_prompts3,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery3]
-#             ).then(
-#                 fn=run_for_prompts4,
-#                 inputs=[face_file,style],
-#                 outputs=[gallery4]
-#             )
-        
-        
-#         gr.Markdown(article)
-
-#     demo.launch(share=True)
-
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("--pretrained_model_name_or_path", type=str, default="wangqixun/YamerMIX_v8")