Upload 12 files

app.py

@@ -4,39 +4,60 @@ from train_tab import create_train_tab
 from virtualtryon_tab import create_virtualtryon_tab
 from faceswap_tab import create_faceswap_tab
 from ipadapter_tab import create_ipadaptor_tab
+from pattern_ip_adapter import sam_zest_tab
 from dotenv import load_dotenv, find_dotenv
 import os 
-
+from src.utils import convert_to_pil
 gallery_list=[]
+
 def update_gallery(img):
+    img=convert_to_pil(img)
+    
     gallery_list.append(img)
     return gallery_list
 
-_ = load_dotenv(find_dotenv())
-with gr.Blocks(theme=gr.themes.Soft(
+
+theme= gr.themes.Soft(
     radius_size=gr.themes.sizes.radius_none,
     primary_hue=gr.themes.colors.emerald, 
-    secondary_hue=gr.themes.colors.green
-                                    )) as demo:
+    secondary_hue=gr.themes.colors.green)
+css = """
+    h1{font-size: 2em}
+    h3{margin-top: 10}
+    #component-1{text-align:left}
+    .main_ui_logged_out{opacity: 0.3; pointer-events: none}
+    .tabitem{border: 20px}
+    .tabitem h1 {
+    font-size: 5em; /* Adjust this value to make the headings bigger */
+}
+
+    .group_padding{padding: .55em}
+    """
+
+_ = load_dotenv(find_dotenv())
+with gr.Blocks(theme=theme,css=css) as demo:
     with gr.Tabs() as tabs:
-        gen_out,move_to_vto,move_to_fs,move_to_ip = create_gen_tab()
+        gen_out,move_to_vto,move_to_fs,move_to_ip,move_to_zest= create_gen_tab()
+        input_ip,output_ip=create_ipadaptor_tab()
         input_vto,output_vto=create_virtualtryon_tab()
+        input_zest,output_zest=sam_zest_tab()
         input_fs,output_fs=create_faceswap_tab()
-        input_ip,output_ip=create_ipadaptor_tab()
-        create_train_tab()
+        #create_train_tab()
      
-    #Buttons 
+
+    # Move to Buttons 
     move_to_vto.click(lambda x:x, inputs=gen_out,outputs=input_vto)      
     move_to_fs.click(lambda x:x, inputs=gen_out,outputs=input_fs)
     move_to_ip.click(lambda x:x, inputs=gen_out,outputs=input_ip)
+    move_to_zest.click(lambda x:x, inputs=gen_out,outputs=input_zest)
 
-    
     #Gallery 
-    image_gallery = gr.Gallery(label="Generated Images Gallery", type="filepath")
-    #Gallery updates  
+    image_gallery = gr.Gallery(label="Generated Images Gallery",type="pil")
+    #Gallery updates  get all outputs 
     gen_out.change(update_gallery,inputs=gen_out,outputs=image_gallery)
     output_vto.change(update_gallery,inputs=output_vto,outputs=image_gallery)
     output_fs.change(update_gallery,inputs=output_fs,outputs=image_gallery)
     output_ip.change(update_gallery,inputs=output_ip,outputs=image_gallery)
+    output_zest.change(update_gallery,inputs=output_zest,outputs=image_gallery)
 
-demo.launch(share=True,debug=True) #,auth=[("username", "password"),(os.getenv("APP_USER"),os.getenv("APP_PW"))])
+demo.launch(share=True,show_error=True,debug=True) #,auth=[("username", "password"),(os.getenv("APP_USER"),os.getenv("APP_PW"))])

faceswap_tab.py

@@ -14,13 +14,7 @@ def create_faceswap_tab():
       with gr.Row():
           face_out = gr.Image(label="Output",type="filepath")
           
-      with gr.Row():
-        examples = gr.Examples(
-                  examples=[
-                      [  "Test_images/person_2.jpg", "Test_images/person_1.jpg"],
-                  ],
-                  inputs=[ fs_base_inp,face_image]
-              )
+     
 
     face_btn.click(fal_faceswap_api,inputs=[fs_base_inp,face_image],outputs=face_out)
 

fal_api.py

@@ -0,0 +1,61 @@
+
+import base64
+from fal_client import FalClient
+from src.utils import numpy_to_base64,resize_image
+import json 
+# Initialize FalClient
+fal_client = FalClient()
+styles_dic= json.dump(open("src/styles.json"))
+
+def fal_api(prompt,ar,nis,seed,style,model="fal-ai/flux-general"):
+  inputs={
+      "prompt":prompt,
+
+      "num_inference_steps":nis,
+
+  }
+  if ar is not None:
+    inputs["image_size"]=ar
+
+  if seed is not None:
+    inputs["seed"]=seed
+  if style is not None:
+    style_type=styles_dic[style][1]
+    if style_type=="model":
+      model=styles_dic[style][0]
+    if style_type=="lora":
+      #inputs["LoraWeight"]=styles_dic[style][0]
+      inputs["loras"]= {  "path": styles_dic[style][0]},
+      if len(styles_dic[style])==3: #Add in prompt triggers
+         inputs["prompt"]+=styles_dic[style][2]
+
+    if style_type=="prompt":
+      inputs["prompt"]+=styles_dic[style][0]
+
+  handler = fal_client.submit(
+        model,
+        arguments=inputs
+    )
+  return handler.get()["images"][0]["url"]
+
+
+def fal_ipadapter_api(input_image,ip_image,seg_prompt):
+  print(input_image,ip_image,seg_prompt)
+
+  handler = fal_client.submit(
+        "comfy/JarvisSan22/cloth_ipadapter",
+        arguments={
+            "loadimage_1":numpy_to_base64(input_image),
+             "loadimage_2":numpy_to_base64(ip_image),
+            "groundingdinosamsegment (segment anything)_prompt":seg_prompt
+        },
+    )
+  print(handler)
+  result= handler.get()
+  #image_urls=[]
+  print(result["outputs"])
+
+  #print(result)
+  return result["outputs"]["20"]["images"][0]["url"]
+
+

gen_tab.py

@@ -1,6 +1,6 @@
 import gradio as gr
 from src.utils import add_to_prompt
-from src.rep_api import generate_image_replicate, model_dict
+from src.rep_api import generate_image_replicate,generate_image_control_net, model_dict
 import os
 
 # The dictionary data
@@ -17,37 +17,71 @@ prompt_dict_kp ={
     "Scene": ["シンプルな白背景", "ファッションランウェイ", "ビジネス会議の中", "宇宙船の内部"]
 }
 
+lora_style_support = [
+     ["ps1","Test_images/lora_support_examples/ps1.png"],
+     ["cyberpunk","Test_images/lora_support_examples/cyberpunk.png"],
+     ["Raylean","Test_images/lora_support_examples/Raylene.png"],
+     ["AppleSeed","Test_images/lora_support_examples/appleseed.png"],
+      ["half-illustration","Test_images/lora_support_examples/halfillust.png"]
+]
+
+prompt_support = [
+    ["Test_images/prompt_support_examples/Man_1.png","A full body photo man  standing with blond hair wearing a suit"],
+    ["Test_images/prompt_support_examples/Woman_1.png","A full body photo girl  standing with blond hair wearing a suit "],
+    ["Test_images/prompt_support_examples/Woman_2.png","a Asian girl as at a fashion show  walking down the cat walk, wearing a red dress"],
+    ["Test_images/prompt_support_examples/Man_2.png","A High exposure photo of a Asian man wearing a blue shirt at a business conference, blue shirt, short black hair, hands out welcoming people into a booth, booth with a green and white color scheme "],
+    ["Test_images/prompt_support_examples/Shoes_1.png","a product photo of high tech shoes with lights and a wifi symbol on the side, low angle shot, front view of walking down stairs "],
+    ["Test_images/prompt_support_examples/Jacket_1.png","a product photo of green checked jacked being on a man from behind , furry collar, large cute character logo of a cat on back of jacket,  simple background,"],
+]
 
 
 def create_gen_tab():
     with gr.TabItem("Image Generator"):
         with gr.Row():
             with gr.Column():
-                inp = gr.Textbox(label="Prompt")
+                inp = gr.Textbox(label="Prompt",info="日本語対応は可能")
+                aspect_ratio = gr.Dropdown(list(["1:1","16:9","9:16","5:4"]),value="1:1", label="Aspect Ratio", info="Aspect Ratio")
+                btn = gr.Button("Generate")
                 with gr.Accordion("extra", open=False):
-                    replicate_api_key = gr.Textbox(
-                        label="Replicate API Key",
-                        info="API key for Replicate",
-                        value=os.environ.get("REPLICATE_API_TOKEN", ""),
-                        type="password",
-                    )
-                    model_type= gr.Dropdown(["dev","schnell"],value="dev",label="flux model base", info="dev - higher quailty but longer \n schnell lower quaility but faster")
+                    #Control net 
+                    use_control_net=gr.Checkbox(label="Use Control net",value=False)
+                    control_net_type=gr.Dropdown(["depth","canny","soft_edge"],value="depth",label="Control net type")
+                    control_net_img= gr.Image(label="Control net image",type="pil")
+                    control_net_strength = gr.Slider(0,1,value=0.4,label="control net strength")
 
-
-                btn = gr.Button("Generate")
+              
             with gr.Column():
-                aspect_ratio = gr.Dropdown(list(["1:1","16:9","9:16","5:4"]),value="1:1", label="Aspect Ratio", info="Aspect Ratio")
+                
                 style_mode = gr.Dropdown(list(model_dict.keys()),label="Style lore",value="Base",info="style model")
+                with gr.Accordion("Style Imgaes",open=False):
+                   # with gr.Column(elem_id="prompt_support_column"):
+                    for i,lora in enumerate(lora_style_support):
+                        if i % 3 == 0:
+                            row = gr.Row()  # Start a new row
+                        with row:
+                            lora_img = gr.Image(value=lora[1], label=lora[0],width=200,height=200, interactive=False)
+                            lora_img.select(lambda x:x, inputs=gr.Textbox(value=lora[0],visible=False),outputs=style_mode)
+                    api_path = gr.Textbox(label="Other_style",info="Style lora safytensor route goes here or replicate link goes here",value=None)
+
                 style_strength = gr.Slider(0,2,value=1,label="Style Strength")
-                api_path = gr.Textbox(label="Other_style",info="Style lora safytensor route goes here or replicate link goes here",value=None)
-                
                 
+
+ 
+
         with gr.Accordion("Prompt Support", open=False):
-            for key, values in prompt_dict.items():
-                with gr.Row():
-                    gr.Button(key,interactive=False)
-                    for value in values:
-                        gr.Button(value).click(add_to_prompt, inputs=[inp, gr.Textbox(value,visible=False)], outputs=inp)
+            for i,item in enumerate(prompt_support):
+                if i % 6 ==0:
+                    row=gr.Row()
+                with row:
+                    with gr.Column(elem_id="prompt_support_column"):
+                        img_ps=gr.Image(value=item[0],label="",interactive=False)
+                        btn_ps=gr.Button(item[1],elem_id="prompt_support_button")
+                        img_ps.select(lambda x:x, inputs=gr.Textbox(item[1],visible=False),outputs=inp)
+                        btn_ps.click(lambda x:x, inputs=gr.Textbox(item[1],visible=False),outputs=inp)
+            
+            #gr.Button(key,interactive=False)
+            #for value in values:
+            #    gr.Button(value).click(add_to_prompt, inputs=[inp, gr.Textbox(value,visible=False)], outputs=inp)
 
         with gr.Row():
             gen_out = gr.Image(label="Generated Image",type="filepath")
@@ -58,7 +92,10 @@ def create_gen_tab():
             move_to_vto =gr.Button("Move to Virtual Try On")    
             move_to_fs =gr.Button("Move to Face Swap") 
             move_to_ip =gr.Button("Move to Cloth IP Adapter")     
+            move_to_zest=gr.Button("Move to Zest IP Adapter")
 
 
-        btn.click(generate_image_replicate, inputs=[inp,style_mode,api_path,aspect_ratio,model_type,style_strength], outputs=[gen_out])
-        return gen_out,move_to_vto,move_to_fs,move_to_ip
+        btn.click(generate_image_control_net, 
+                  inputs=[inp,style_mode,api_path,aspect_ratio,style_strength,use_control_net,control_net_type,control_net_img,control_net_strength], 
+                  outputs=[gen_out])
+        return gen_out,move_to_vto,move_to_fs,move_to_ip,move_to_zest

ipadapter_tab.py

@@ -1,55 +1,57 @@
-from src.fal_api import fal_ipadapter_api
-import gradio as gr
-
-
-def create_ipadaptor_tab():
-    
-    with gr.TabItem("Cloth IP Adapter",id="cloth_ip_adapter"):
-      with gr.Row():
-        with gr.Column():
-          api_inp = gr.Image(label="Base Image")
-          ap_prompt = gr.Textbox(label="clothe prompt")
-          with gr.Accordion("Example People", open=False):
-                    human_examples = gr.Examples(
-                         examples=[
-                            ["Test_images/Woman_1.png"],
-                            ["Test_images/man_1.png"],
-                            ["Test_images/Woman_2.png"],
-                         
-                            ["Test_images/Woman_3.png"],
-                      
-                            ["Test_images/Woman_4.png"],
-                             ["Test_images/Woman_5.png"],
-                            ["Test_images/anime_woman_1.png"],
-                             ["Test_images/anime_woman_2.png"],
-                            ["Test_images/anime_woman_3.png"],
-                            ["Test_images/Jump.png"],
-                            ["Test_images/Walk_1.png"],
-                            ["Test_images/Walk_2.png"],
-                            ["Test_images/Walk_girl_1.png"],
-                            ["Test_images/Walk_girl_2.png"]
-                        ],
-                        inputs=[api_inp]
-                    )
-        
-        with gr.Column():
-          ip_image = gr.Image(label="IP Adapter Image")
-          ip_btn = gr.Button("Process")
-          with gr.Accordion("Example Stles and clothes ", open=False):
-                    ip_examples = gr.Examples(
-                        examples=[
-                            ["Test_images/style_1.jpg"],
-                            ["Test_images/style_2.png"],
-                            ["Test_images/Style_3.png"],
-                            ["Test_images/Style_4.png"],
-                            ["Test_images/dress_5.png"],
-                            ["Test_images/Jacket_1.png"]
-                        ],
-                        inputs=[ip_image]
-                    )
-      with gr.Row():
-          api_out = gr.Image(label="Output",type="filepath")
-
-    ip_btn.click(fal_ipadapter_api,inputs=[api_inp,ip_image,ap_prompt],outputs=api_out)
-
+from src.fal_api import fal_ipadapter_api
+import gradio as gr
+
+
+def create_ipadaptor_tab():
+    
+    with gr.TabItem("Cloth IP Adapter",id="cloth_ip_adapter"):
+      with gr.Row():
+        with gr.Column():
+          api_inp = gr.Image(label="Base Image")
+          ap_prompt = gr.Textbox(label="clothe prompt")
+          with gr.Accordion("Example People", open=False):
+                    human_examples = gr.Examples(
+                         examples=[
+                            ["Test_images/Woman_1.png"],
+                            ["Test_images/man_1.jpg"],
+                            ["Test_images/Woman_2.png"],
+                            ["Test_images/person_2.jpg"],
+                            ["Test_images/Woman_3.png"],
+                            ["Test_images/man_1.png"],
+                            ["Test_images/Woman_4.png"],
+                             ["Test_images/Woman_5.png"],
+                            ["Test_images/anime_woman_1.png"],
+                             ["Test_images/anime_woman_2.png"],
+                            ["Test_images/anime_woman_3.png"],
+                            ["Test_images/Jump.png"],
+                            ["Test_images/Walk_1.png"],
+                            ["Test_images/Walk_2.png"],
+                            ["Test_images/Walk_girl_1.png"],
+                            ["Test_images/Walk_girl_2.png"]
+                        ],
+                        inputs=[api_inp]
+                    )
+        
+        with gr.Column():
+          ip_image = gr.Image(label="IP Adapter Image")
+          ip_btn = gr.Button("Process")
+          with gr.Accordion("Example Stles and clothes ", open=False):
+                    ip_examples = gr.Examples(
+                        examples=[
+                            ["Test_images/style_1.jpg"],
+                            ["Test_images/style_2.png"],
+                            ["Test_images/Style_3.png"],
+                            ["Test_images/Style_4.png"],
+                            ["Test_images/pattern_1.png"],
+                            ["Test_images/pattern_2.jpg"],
+                            ["Test_images/pattern_3.jpg"],
+                            ["Test_images/pattern_4.jpg"],
+                        ],
+                        inputs=[ip_image]
+                    )
+      with gr.Row():
+          api_out = gr.Image(label="Output",type="filepath")
+
+    ip_btn.click(fal_ipadapter_api,inputs=[api_inp,ip_image,ap_prompt],outputs=api_out)
+
     return api_inp,api_out

model_dict.json

@@ -1,8 +1,8 @@
-{
-  "Base":"xlabs-ai/flux-dev-realism:39b3434f194f87a900d1bc2b6d4b983e90f0dde1d5022c27b52c143d670758fa",
-  "ps1":"veryvanya/flux-ps1-style:e785bcd326ea7a2c6efef8c43122a289f2c344370a4b74b2c7fa1a5ff4c38fea",
-  "mystic-animals":"halimalrasihi/flux-mystic-animals:294de709b06655e61bb0149ec61ef8b5d3ca030517528ac34f8252b18b09b7ad",
-  "cyberpunk":"fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180",
-  "Raylean": "jarvis-labs2024/flux-raylene:5574556226d11e0f10855a957d91f118a9178c8fc77e7e7b18830627ce3184f1",
-  "AppleSeed": "jarvis-labs2024/flux-appleseed:0aecb9fdfb17a2517112cc70b4a1898aa7791da84a010419782ce7043481edec"
-}
+{
+    "Base":["xlabs-ai/flux-dev-realism:39b3434f194f87a900d1bc2b6d4b983e90f0dde1d5022c27b52c143d670758fa","https://huggingface.co/XLabs-AI/flux-RealismLora/resolve/main/lora.safetensors","REALISM"],
+    "ps1":["veryvanya/flux-ps1-style:e785bcd326ea7a2c6efef8c43122a289f2c344370a4b74b2c7fa1a5ff4c38fea","https://huggingface.co/veryVANYA/ps1-style-flux/resolve/main/ps1_style_flux_v1.safetensors","ps1 game screenshot"],
+    "cyberpunk":["fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180","https://huggingface.co/fofr/flux-80s-cyberpunk/resolve/main/lora.safetensors","style of 80s cyberpunk"],
+    "Raylean": ["jarvis-labs2024/flux-raylene:5574556226d11e0f10855a957d91f118a9178c8fc77e7e7b18830627ce3184f1","https://replicate.delivery/yhqm/jpM5dp9JqOoYPdvF2lXsdWC0cV0XBHWQHmflBYz9L3IegyTTA/trained_model.tar"," SOK"],
+    "AppleSeed": ["jarvis-labs2024/flux-appleseed:0aecb9fdfb17a2517112cc70b4a1898aa7791da84a010419782ce7043481edec","https://replicate.delivery/yhqm/6v6JOdXtArJZEBbsjPoYSC6lezM2Is12eghIoQBhlnWNI0UTA/trained_model.tar","style of APPLESEED anime"],
+    "half-illustration":["davisbrown/flux-half-illustration:687458266007b196a490e79a77bae4b123c1792900e1cb730a51344887ad9832","https://huggingface.co/davisbro/half_illustration/resolve/main/flux_train_replicate.safetensors?download=true","In the style of TOK,vibrant illustration"]
+}

pattern_ip_adapter.py

@@ -0,0 +1,47 @@
+import gradio as gr 
+from src.rep_api import sam_segment,replicate_zest
+from src.utils import open_image_from_url,image_to_base64,cut_alpha_from_image
+from src.utils import convert_to_pil
+
+def sam_zest(image,prompt,negative_prompt,material_img):
+    outputs=sam_segment(image,prompt,negative_prompt)
+    mask = open_image_from_url(outputs["inverted_mask"])
+    mask_ = mask.convert("L").point(lambda x: 255 - x)
+    img=image.copy()
+    img=convert_to_pil(img)
+    img.putalpha(mask_)
+    output=replicate_zest(cut_alpha_from_image(img),material_img=material_img)
+    zest_img=open_image_from_url(output)
+    zest_img=zest_img.resize((img.size))
+    zest_img.putalpha(mask_)
+    image.paste(zest_img,(0,0),mask_)
+    return image 
+
+def sam_zest_tab():
+    with gr.TabItem("Zest Segment",id="zest_seg"):
+        with gr.Row():
+            with gr.Column():
+                image=gr.Image(label="Base Image")
+                seg_prompt=gr.Textbox(label="Segment area")
+                seg_negative=gr.Textbox(label="Dont seg area")
+
+                zest_image=gr.Image(label="Zest image")
+                zest_examples= gr.Examples(
+                        examples=[
+                            "https://replicate.delivery/pbxt/Kl23gJODaW7EuxrDzBG9dcgqRdMaYSWmBQ9UexnwPiL7AnIr/3.jpg",
+                            "https://replicate.delivery/pbxt/Kl2WefehduxwWcQc5OrrBH6AkojQ6OqyQSKBvBLrroSpEBim/f2f0488a-180e-4d7e-9907-f26f92ac5f16.jpg",
+                            "https://replicate.delivery/pbxt/Kl2VlUibviSP8Kq5ULLJmMOWorog1YFu0zTreqhqX97c62ku/572a1fc9-a114-4d5b-8c7c-85aa5648c7b4.jpg",
+                            "https://replicate.delivery/pbxt/Kl2VCw1UVIJsYw9r8iqSYUMm65ePJhfYOLNolOE8CwxfRjX2/28481ff0-0829-42af-a658-fb96be2abb3d.jpg",
+                             "Test_images/pattern_1.png",
+                            "Test_images/pattern_2.jpg",
+                            "Test_images/pattern_3.jpg",
+                            "Test_images/pattern_4.jpg"],
+
+                        inputs=[zest_image])
+            with gr.Column():
+                gen_zest=gr.Button("Add ZEST")
+                output_img=gr.Image(label="output")
+            
+            gen_zest.click(sam_zest,inputs=[image,seg_prompt,seg_negative,zest_image],outputs=[output_img])
+    return image,output_img
+            

requirments.txt

@@ -0,0 +1,8 @@
+gradio
+fal
+fal-client
+numpy
+replicate
+python-dotenv
+langdetect 
+deepl

style_tab.py

@@ -0,0 +1,24 @@
+import gradio as gr
+
+def create_style_tab(demo):
+    with gr.TabItem("Style Customization"):
+        theme_dropdown = gr.Dropdown(choices=["Default", "Glass", "Monochrome", "Soft"], label="Choose a Theme")
+        custom_css = gr.Textbox(label="Custom CSS", placeholder="Enter custom CSS here...")
+        apply_button = gr.Button("Apply Style")
+
+        def apply_style(theme, css):
+            if theme == "Default":
+                demo.theme = gr.themes.Default()
+            elif theme == "Glass":
+                demo.theme = gr.themes.Glass()
+            elif theme == "Monochrome":
+                demo.theme = gr.themes.Monochrome()
+            elif theme == "Soft":
+                demo.theme = gr.themes.Soft()
+            
+            if css:
+                demo.css = css
+
+        apply_button.click(apply_style, inputs=[theme_dropdown, custom_css], outputs=[])
+
+    return demo

virtualtryon_tab.py

@@ -7,16 +7,18 @@ def create_virtualtryon_tab():
         with gr.Row():
             with gr.Column():
                 human_img =  gr.Image(label="Human Image")
-                crop = gr.Checkbox(label="Crop", value=False)
+                crop = gr.Checkbox(label="Crop", value=True)
                 seed = gr.Number(label="Seed", value=42)
                 steps = gr.Number(label="Steps", value=30)
+                category = gr.Dropdown(["upper_body", "lower_body", "dresses"], label="Category", value="upper_body")
+                garment_des = gr.Textbox(label="Garment Description")
                 with gr.Accordion("Example People", open=False):
                     human_examples = gr.Examples(
                         examples=[
                             ["Test_images/Woman_1.png"],
-                            ["Test_images/person_1.jpg"],
+                            ["Test_images/prompt_support_examples/Man_1.png"],
                             ["Test_images/Woman_2.png"],
-                            ["Test_images/person_2.jpg"],
+                            ["Test_images/prompt_support_examples/Man2_2.png"],
                             ["Test_images/Woman_3.png"],
                             ["Test_images/man_1.png"],
                             ["Test_images/Woman_4.png"],
@@ -25,19 +27,15 @@ def create_virtualtryon_tab():
                              ["Test_images/anime_woman_2.png"],
                             ["Test_images/anime_woman_3.png"],
                             ["Test_images/Jump.png"],
-                            ["Test_images/Walk_1.png"],
-                            ["Test_images/Walk_2.png"],
-                            ["Test_images/Walk_girl_1.png"],
-                            ["Test_images/Walk_girl_2.png"]
+                           
+                       
                         ],
                         inputs=[human_img],
                          examples_per_page=24
                     )
             with gr.Column():
                 garm_img = gr.Image(label="Garment Image")
-                category = gr.Dropdown(["upper_body", "lower_body", "dresses"], label="Category", value="upper_body")
-                garment_des = gr.Textbox(label="Garment Description")
-                with gr.Accordion("Example Clothes", open=False):
+                with gr.Accordion("Example Clothes", open=True):
                     cloth_examples = gr.Examples(
                         examples=[
                             ["Test_images/pink_jumper.png","pink jumper","upper_body"],