Upload 140 files

.gitattributes

@@ -87,3 +87,4 @@ Test_images/example_outputs/Re_light_output5.png filter=lfs diff=lfs merge=lfs -
 Test_images/IP_Material_2.jpg filter=lfs diff=lfs merge=lfs -text
 Test_images/lora_support_examples/Galverse.png filter=lfs diff=lfs merge=lfs -text
 Test_images/Skirt_1.png filter=lfs diff=lfs merge=lfs -text
+HowTo/Gen.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -23,6 +23,10 @@ os.makedirs(base_dir, exist_ok=True)
 
 # Function to convert and save the image to a dated folder, and update the gallery
 def update_gallery_local(img):
+    
+    if img is None:
+        return gallery_list
+    
     print(type(img), len(gallery_list))
 
     try:

gen_tab.py

@@ -50,6 +50,7 @@ def create_gen_tab():
                                 "4. Options in extra control net. Extraでコントロールネットのオプションを選択します。\n"
                                 "5. Click 'Generate' to create the image. Generateをクリックして画像を生成します。\n"
                                 "6. click button to move image to other tab.ボタンをクリックして画像を他のタブに移動します。 \n")
+                    gr.Image(value="HowTo/Gen.png",label=None,interactive=False)
         #Gen generatpor options 
         with gr.Row():
             with gr.Column():

ipadapter_tab.py

@@ -1,93 +1,90 @@
-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.Accordion("HowTo",open=False):
-        gr.Markdown("""
-        # Cloth IP Adapter 服のIPアタォーター \n
-        ・1 Select base image  ベース画像を選択します。 \n
-        ・2 Prompt area you want the IP to be applied IPを適用するためのプロンプトエリアを選択します。 \n
-        ・3 Select IP image   IP画像を選択します。 \n
-        ・4 Click Generate  生成をクリックします。 \n
-      
-        """)
-        gr.Image(value="HowTo/Flow_IP_ClothAdapter.jpg",label=None,interactive=False)
-        
-
-      with gr.Row():
-        with gr.Column():
-          api_inp = gr.Image(label="Base Image")
-          
-          with gr.Accordion("Example base images", open=False):
-                    human_examples = gr.Examples(
-                         examples=[
-                            ["Test_images/Woman_1.png"],
-                            ["Test_images/man_1.png"],
-                            ["Test_images/example_outputs/input_4.png"],
-                            ["Test_images/Woman_2.png"],
-                            ["Test_images/Woman_3.png"],
-                            ["Test_images/man_2.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_3.png"],
-                            ["Test_images/Walk_4.png"]
-                        ],
-                        inputs=[api_inp],
-                         examples_per_page=14
-                    )
-        
-        with gr.Column():
-          ip_image = gr.Image(label="IP Adapter Image")
-          
-          with gr.Accordion("Example IP images ", 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"],
-                            ["Test_images/Jacket_1.png"],
-                            ["Test_images/Suit_4.png"],
-                            ["Test_images/dress_5.png"],
-                            ["Test_images/Shirt_1.png"],
-                            ["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"],
-                        ],
-                        inputs=[ip_image],
-                         examples_per_page=14
-                    )
-      with gr.Row():
-        ap_prompt = gr.Textbox(label="clothes prompt",value="clothes",info="Clothe are you want to use 希望の服のエリア (日本語可能)")
-      with gr.Row():
-          ip_btn = gr.Button("Generate",elem_id="gen_btn")
-      with gr.Row():
-          api_out = gr.Image(label="Output",type="filepath",elem_id="output_image")
-      with gr.Row(): #Move gen out row
-            
-            move_to_cnmk =gr.Button("Move to Control net mockup ")
-            move_to_relight= gr.Button("Move to Relight")
-   
-
-      with gr.Row():
-            gr.Examples(examples=[
-                ["Test_images/example_outputs/input_4.png","Test_images/Jacket_1.png","Jacket","Test_images/example_outputs/output_clothIP_1.png"],
-                ["Test_images/Woman_2.png","Test_images/pattern_4.jpg","Dress","Test_images/example_outputs/output_clothIP_2.png"],
-            ],inputs=[api_inp,ip_image,ap_prompt,api_out])
-      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.Accordion("HowTo",open=False):
+        gr.Markdown("""
+        # Cloth IP Adapter 服のIPアタォーター \n
+        ・1 Select base image  ベース画像を選択します。 \n
+        ・2 Prompt area you want the IP to be applied IPを適用するためのプロンプトエリアを選択します。 \n
+        ・3 Select IP image   IP画像を選択します。 \n
+        ・4 Click Generate  生成をクリックします。 \n
+      
+        """)
+        gr.Image(value="HowTo/Flow_IP_ClothAdapter.jpg",label=None,interactive=False)
+        
+
+      with gr.Row():
+        with gr.Column():
+          api_inp = gr.Image(label="Base Image")
+          
+          with gr.Accordion("Example base images", open=True):
+                    human_examples = gr.Examples(
+                         examples=[
+                             ["Test_images/example_outputs/input_4.png"],
+                            ["Test_images/man_1.png"],
+                            ["Test_images/Woman_2.png"],
+                            ["Test_images/Woman_3.png"],
+                            ["Test_images/man_2.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/Walk_1.png"],
+                            ["Test_images/Walk_2.png"],
+                            ["Test_images/Walk_3.png"],
+                            ["Test_images/Walk_4.png"]
+                        ],
+                        inputs=[api_inp],
+                         examples_per_page=14
+                    )
+        
+        with gr.Column():
+          ip_image = gr.Image(label="IP Adapter Image")
+          
+          with gr.Accordion("Example IP images ", open=True):
+                    ip_examples = gr.Examples(
+                        examples=[
+                              ["Test_images/Jacket_1.png"],
+                            ["Test_images/Suit_4.png"],
+                            ["Test_images/dress_5.png"],
+                            ["Test_images/Shirt_1.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"],
+                          
+                            ["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"],
+                            
+                        ],
+                        inputs=[ip_image],
+                         examples_per_page=14
+                    )
+      with gr.Row():
+        ap_prompt = gr.Textbox(label="clothes prompt",value="clothes",info="Clothe are you want to use 希望の服のエリア (日本語可能)")
+      with gr.Row():
+          ip_btn = gr.Button("Generate",elem_id="gen_btn")
+      with gr.Row():
+          api_out = gr.Image(label="Output",type="filepath",elem_id="output_image")
+      with gr.Row(): #Move gen out row
+            
+            move_to_cnmk =gr.Button("Move to Control net mockup ")
+            move_to_relight= gr.Button("Move to Relight")
+    
+
+      with gr.Row():
+          gr.Examples(examples=[
+              ["Test_images/example_outputs/input_4.png","Test_images/Jacket_1.png","Jacket","Test_images/example_outputs/output_clothIP_1.png"],
+              ["Test_images/Woman_2.png","Test_images/pattern_4.jpg","Dress","Test_images/example_outputs/output_clothIP_2.png"],
+          ],inputs=[api_inp,ip_image,ap_prompt,api_out])
+    ip_btn.click(fal_ipadapter_api,inputs=[api_inp,ip_image,ap_prompt],outputs=api_out)
     return api_inp,api_out,move_to_cnmk,move_to_relight

src/rep_api.py

@@ -12,7 +12,12 @@ def generate_image_control_net(prompt,lora_model,api_path,aspect_ratio,lora_scal
                               use_control_net,control_net_type,control_net_img,control_net_strength, 
                              num_outputs=1,guidance_scale=3.5,seed=None,                
 ): 
-   print(prompt,lora_model,api_path,aspect_ratio,use_control_net)
+   #print(prompt,lora_model,api_path,aspect_ratio,use_control_net)
+   #print(prompt,len(prompt),type(prompt),prompt is None)
+   if len(prompt)==0:
+      prompt=os.environ["default_promt"]
+   #print(prompt,lora_model,api_path,aspect_ratio)
+      
    inputs = {
        "prompt": detect_and_translate(prompt),
         "output_format": "png",
@@ -51,7 +56,7 @@ def generate_image_control_net(prompt,lora_model,api_path,aspect_ratio,lora_scal
      api_path,
      input=inputs
    )
-   print(output)
+   #print(output)
    return output[0]
 
    
@@ -61,8 +66,10 @@ def generate_image_replicate(prompt,lora_model,api_path,aspect_ratio,model,lora_
                              num_outputs=1,guidance_scale=3.5,seed=None,
 
                              ):
-  print(prompt,lora_model,api_path,aspect_ratio)
-
+  #print(prompt,len(prompt),type(prompt),prompt is None)
+  if len(prompt)==0:
+    prompt=os.environ["default_promt"]
+  #print(prompt,lora_model,api_path,aspect_ratio)
   #if model=="dev":
   num_inference_steps=30
   if model=="schnell":
@@ -87,7 +94,7 @@ def generate_image_replicate(prompt,lora_model,api_path,aspect_ratio,model,lora_
     api_path,
     input=inputs
   )
-  print(output)
+  #print(output)
   return output[0]
 def replicate_bgcontrolnet(img,prompt,background_prompt, sampler_name= "DPM++ SDE Karras",
         negative_prompt="(deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, mutated hands and fingers:1.4), (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, disconnected limbs, mutation, mutated, ugly, disgusting, amputation"
@@ -108,7 +115,7 @@ def replicate_bgcontrolnet(img,prompt,background_prompt, sampler_name= "DPM++ SD
     return output["image"]
 
 def replicate_caption_api(image,model,context_text):
-  print(model,context_text)
+  #print(model,context_text)
   base64_image = image_to_base64(image)
   if model=="blip":
     output = replicate.run(
@@ -121,7 +128,7 @@ def replicate_caption_api(image,model,context_text):
         "use_nucleus_sampling": False
     }
     )
-    print(output)
+    #print(output)
 
   elif model=="llava-16":
     output = replicate.run(
@@ -135,7 +142,7 @@ def replicate_caption_api(image,model,context_text):
             "temperature": 0.2
           }
         )
-    print(output)
+    #print(output)
     output = "".join(output)
 
   elif model=="img2prompt":
@@ -145,7 +152,7 @@ def replicate_caption_api(image,model,context_text):
         "image":base64_image
         }
     )
-    print(output)
+    #print(output)
   return output
 
 def update_replicate_api_key(api_key):
@@ -168,7 +175,7 @@ def virtual_try_on(crop, seed, steps, category,  garm_img, human_img,  garment_d
             "garment_des": garment_des
         }
     )
-    print(output)
+    #print(output)
     return output
 
 
@@ -180,7 +187,7 @@ def process_images(files,model,context_text,token_string):
     images = []
     textbox =""
     for file in files:
-        print(file)
+        #print(file)
         image = Image.open(file)
         if model=="None":
            caption="[Insert cap here]"
@@ -217,7 +224,7 @@ def traning_function(zip_path,training_model,training_destination,seed,token_str
   BB_defult="https://f005.backblazeb2.com/file/"
   if BB_defult not in zip_path:
     zip_path=BB_uploadfile(zip_path,os.path.basename(zip_path),BB_bucket_name)
-  print(zip_path)
+  #print(zip_path)
   training_logs = f"Using zip traning file at: {zip_path}\n"
   yield training_logs, None
   input={
@@ -230,11 +237,11 @@ def traning_function(zip_path,training_model,training_destination,seed,token_str
               "seed": seed,
               "input_images": zip_path
           }
-  print(training_destination)
+  #print(training_destination)
   username,model_name=training_destination.split("/")
   assert replicate_create_model(username,model_name,visibility="private",hardware="gpu-a40-large"),"Error in creating model on replicate, check API key and username is correct "
 
-  print(input)
+  #print(input)
   try:
       training = replicate.trainings.create(
           destination=training_destination,
@@ -293,7 +300,7 @@ def sam_segment(image,prompt,negative_prompt,adjustment_factor=-15):
   out_items={}
   for item in output:
     # https://replicate.com/schananas/grounded_sam/api#output-schema
-    print(item)
+    #print(item)
     out_items[os.path.basename(item).split(".")[0]]=item
   return out_items 
 
@@ -311,7 +318,7 @@ def replicate_zest(img,material_img="https://replicate.delivery/pbxt/Kl23gJODaW7
           "material_image":material_img
       }
   ) 
-  print(output)
+  #print(output)
   return output
 
 
@@ -334,7 +341,7 @@ def replicate_iclight_BG(img,prompt,bg_img,light_source="Use Background Image",
   ):
     assert light_source in light_source_options, "Please select a correct ligh source option"
     width, height = img.size
-    print(width,height)
+    #print(width,height)
     img=image_to_base64(img)
     #if light_source=="Use Background Image":
     if bg_img is None:

virtualtryon_tab.py

@@ -21,30 +21,32 @@ def create_virtualtryon_tab():
                 human_img =  gr.Image(label="Human Image")
                 crop = gr.Checkbox(label="Crop", value=True)
                 seed = gr.Number(label="Seed", value=42)
+            with gr.Column():
                 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/prompt_support_examples/Man_1.png"],
-                            ["Test_images/Woman_2.png"],
-                            ["Test_images/prompt_support_examples/Man_2.png"],
-                            ["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"],
-                           
-                       
-                        ],
-                        inputs=[human_img],
-                         examples_per_page=24
-                    )
+        with gr.Row():
+            with gr.Accordion("Example People", open=False):
+                human_examples = gr.Examples(
+                    examples=[
+                        ["Test_images/Woman_1.png"],
+                        ["Test_images/prompt_support_examples/Man_1.png"],
+                        ["Test_images/Woman_2.png"],
+                        ["Test_images/prompt_support_examples/Man_2.png"],
+                        ["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"],
+                        
+                    
+                    ],
+                    inputs=[human_img],
+                        examples_per_page=24
+                )
             with gr.Column():
                 garm_img = gr.Image(label="Garment Image")
                 with gr.Accordion("Example Clothes", open=True):