Update flux_schnell.py

flux_schnell.py

@@ -28,95 +28,105 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_in
     ).images[0] 
     return image, seed
  
-examples = [
-    "a tiny astronaut hatching from an egg on the moon",
-    "a cat holding a sign that says hello world",
-    "an anime illustration of a wiener schnitzel",
-]
 
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
-
-with gr.Blocks(css=css) as demo:
+def create_flux_tab(image_input):
+    examples = [
+        "a tiny astronaut hatching from an egg on the moon",
+        "a cat holding a sign that says hello world",
+        "an anime illustration of a wiener schnitzel",
+    ]
     
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [schnell]
-12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
-[[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
-        """)
-        
-        with gr.Row():
-            
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            
-            run_button = gr.Button("Run", scale=0)
-        
-        result = gr.Image(label="Result", show_label=False)
+    css="""
+    #col-container {
+        margin: 0 auto;
+        max-width: 520px;
+    }
+    """
+    
+    with gr.Blocks(css=css) as demo:
         
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+        with gr.Column(elem_id="col-container"):
+            gr.Markdown(f"""# FLUX.1 [schnell]""")
             
             with gr.Row():
                 
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
                 )
                 
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
+                run_button = gr.Button("Run", scale=0)
             
-            with gr.Row():
+            result = gr.Image(label="Result", show_label=False
+
+             with gr.Row():
+                use_in_text2lipsync_button = gr.Button("이 이미지를 Txt to Lipsync 탭에서 사용하기")  # 새로운 버튼 추가
+            
+            
+            with gr.Accordion("Advanced Settings", open=False):
                 
-  
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
+                seed = gr.Slider(
+                    label="Seed",
+                    minimum=0,
+                    maximum=MAX_SEED,
                     step=1,
-                    value=4,
+                    value=0,
                 )
-        
-        gr.Examples(
-            examples = examples,
+                
+                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                
+                with gr.Row():
+                    
+                    width = gr.Slider(
+                        label="Width",
+                        minimum=256,
+                        maximum=MAX_IMAGE_SIZE,
+                        step=32,
+                        value=1024,
+                    )
+                    
+                    height = gr.Slider(
+                        label="Height",
+                        minimum=256,
+                        maximum=MAX_IMAGE_SIZE,
+                        step=32,
+                        value=1024,
+                    )
+                
+                with gr.Row():
+                    
+      
+                    num_inference_steps = gr.Slider(
+                        label="Number of inference steps",
+                        minimum=1,
+                        maximum=50,
+                        step=1,
+                        value=4,
+                    )
+            
+            gr.Examples(
+                examples = examples,
+                fn = infer,
+                inputs = [prompt],
+                outputs = [result, seed],
+                cache_examples="lazy"
+            )
+    
+        gr.on(
+            triggers=[run_button.click, prompt.submit],
             fn = infer,
-            inputs = [prompt],
-            outputs = [result, seed],
-            cache_examples="lazy"
+            inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
+            outputs = [result, seed]
         )
-
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
-        outputs = [result, seed]
-    )
+        # 새로운 버튼 클릭 이벤트 정의
+        use_in_text2lipsync_button.click(
+            fn=lambda img: img,  # 간단한 람다 함수를 사용하여 이미지를 그대로 전달
+            inputs=[result],  # 생성된 이미지를 입력으로 사용
+            outputs=[image_input]  # Text to LipSync 탭의 image_input을 업데이트
+        
+    return flux_demo
 
 # demo.launch()