Update app.py

app.py

@@ -425,227 +425,165 @@ def generate_image(
 
     return images[0], gr.update(visible=True)
 
-# Description
+# SIMPLIFIED PROFESSIONAL UI
 title = r"""
-<h1 align="center">InstantID: Zero-shot Identity-Preserving Generation in Seconds</h1>
+<h1 align="center">🎯 Pro AI Headshot Generator</h1>
 """
 
 description = r"""
-<b>Official 🤗 Gradio demo</b> for <a href='https://github.com/InstantID/InstantID' target='_blank'><b>InstantID: Zero-shot Identity-Preserving Generation in Seconds</b></a>.<br>
-We are organizing a Spring Festival event with HuggingFace from 2.7 to 2.25, and you can now generate pictures of Spring Festival costumes. Happy Dragon Year 🐲 ! Share the joy with your family.<br>
-How to use:<br>
-1. Upload an image with a face. For images with multiple faces, we will only detect the largest face. Ensure the face is not too small and is clearly visible without significant obstructions or blurring.
-2. (Optional) You can upload another image as a reference for the face pose. If you don't, we will use the first detected face image to extract facial landmarks. If you use a cropped face at step 1, it is recommended to upload it to define a new face pose.
-3. (Optional) You can select multiple ControlNet models to control the generation process. The default is to use the IdentityNet only. The ControlNet models include pose skeleton, canny, and depth. You can adjust the strength of each ControlNet model to control the generation process.
-4. Enter a text prompt, as done in normal text-to-image models.
-5. Click the <b>Submit</b> button to begin customization.
-6. Share your customized photo with your friends and enjoy! 😊"""
-
-article = r"""
----
-📝 **Citation**
-<br>
-If our work is helpful for your research or applications, please cite us via:
-```bibtex
-@article{wang2024instantid,
-  title={InstantID: Zero-shot Identity-Preserving Generation in Seconds},
-  author={Wang, Qixun and Bai, Xu and Wang, Haofan and Qin, Zekui and Chen, Anthony},
-  journal={arXiv preprint arXiv:2401.07519},
-  year={2024}
-}
-```
-📧 **Contact**
-<br>
-If you have any questions, please feel free to open an issue or directly reach us out at <b>haofanwang.ai@gmail.com</b>.
-"""
+<b>Transform any selfie into professional headshots in seconds</b><br>
+Perfect for LinkedIn, corporate profiles, and professional portfolios.<br><br>
 
-tips = r"""
-### Usage tips of InstantID
-1. If you're not satisfied with the similarity, try increasing the weight of "IdentityNet Strength" and "Adapter Strength."    
-2. If you feel that the saturation is too high, first decrease the Adapter strength. If it remains too high, then decrease the IdentityNet strength.
-3. If you find that text control is not as expected, decrease Adapter strength.
-4. If you find that realistic style is not good enough, go for our Github repo and use a more realistic base model.
+<strong>🎯 How to get perfect headshots:</strong><br>
+1. <b>Upload</b> a clear photo of your face<br>
+2. <b>Choose</b> your preferred style<br>
+3. <b>Click Generate</b> and download your professional headshots<br><br>
+
+<em>No technical knowledge needed - we handle all the complex AI settings automatically!</em>
 """
 
 css = """
 .gradio-container {width: 85% !important}
+.instructions {background: #f0f8ff; padding: 15px; border-radius: 10px; border-left: 4px solid #3b82f6;}
 """
+
 with gr.Blocks(css=css) as demo:
-    # description
     gr.Markdown(title)
-    gr.Markdown(description)
-
+    
     with gr.Row():
-        with gr.Column():
-            with gr.Row(equal_height=True):
-                # upload face image
+        with gr.Column(scale=1):
+            # Instructions Box
+            with gr.Group():
+                gr.Markdown("""
+                <div class="instructions">
+                <h3>📸 Photo Tips for Best Results:</h3>
+                • Clear, well-lit face photo<br>
+                • Face should be visible and not too small<br>
+                • Avoid blurry or dark images<br>
+                • Single person in photo works best
+                </div>
+                """)
+            
+            # Simple Upload Section
+            with gr.Group():
+                gr.Markdown("### 1️⃣ Upload Your Photo")
                 face_file = gr.Image(
-                    label="Upload a photo of your face", type="filepath"
-                )
-                # optional: upload a reference pose image
-                pose_file = gr.Image(
-                    label="Upload a reference pose image (Optional)",
+                    label="Upload your photo",
                     type="filepath",
+                    height=200
                 )
-
-            # prompt
-            prompt = gr.Textbox(
-                label="Prompt",
-                info="Give simple prompt is enough to achieve good face fidelity",
-                placeholder="A photo of a person",
-                value="",
-            )
-
-            submit = gr.Button("Submit", variant="primary")
-            enable_LCM = gr.Checkbox(
-                label="Enable Fast Inference with LCM", value=enable_lcm_arg,
-                info="LCM speeds up the inference step, the trade-off is the quality of the generated image. It performs better with portrait face images rather than distant faces",
-            )
-            style = gr.Dropdown(
-                label="Style template",
-                choices=STYLE_NAMES,
-                value=DEFAULT_STYLE_NAME,
-            )
-
-            # strength
-            identitynet_strength_ratio = gr.Slider(
-                label="IdentityNet strength (for fidelity)",
-                minimum=0,
-                maximum=1.5,
-                step=0.05,
-                value=0.80,
-            )
-            adapter_strength_ratio = gr.Slider(
-                label="Image adapter strength (for detail)",
-                minimum=0,
-                maximum=1.5,
-                step=0.05,
-                value=0.80,
-            )
-            with gr.Accordion("Controlnet"):
-                controlnet_selection = gr.CheckboxGroup(
-                    ["canny", "depth"], label="Controlnet", value=["depth"],
-                    info="Use pose for skeleton inference, canny for edge detection, and depth for depth map estimation. You can try all three to control the generation process"
-                )
-                # pose_strength = gr.Slider(
-                #     label="Pose strength",
-                #     minimum=0,
-                #     maximum=1.5,
-                #     step=0.05,
-                #     value=0.40,
-                # )
-                canny_strength = gr.Slider(
-                    label="Canny strength",
-                    minimum=0,
-                    maximum=1.5,
-                    step=0.05,
-                    value=0.40,
-                )
-                depth_strength = gr.Slider(
-                    label="Depth strength",
-                    minimum=0,
-                    maximum=1.5,
-                    step=0.05,
-                    value=0.40,
-                )
-            with gr.Accordion(open=False, label="Advanced Options"):
-                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",
+                
+            # Style Selection
+            with gr.Group():
+                gr.Markdown("### 2️⃣ Choose Style")
+                style = gr.Dropdown(
+                    label="Professional Style",
+                    choices=STYLE_NAMES,
+                    value="Professional",
+                    info="Select the look you want for your headshots"
                 )
-                num_steps = gr.Slider(
-                    label="Number of sample steps",
-                    minimum=1,
-                    maximum=100,
-                    step=1,
-                    value=5 if enable_lcm_arg else 30,
+                
+            # Simple Settings (Hidden Advanced Options)
+            with gr.Accordion("⚙️ Advanced Settings (Optional)", open=False):
+                prompt = gr.Textbox(
+                    label="Custom Description",
+                    placeholder="e.g., 'professional business headshot'",
+                    value="professional headshot",
+                    info="Describe how you want to appear"
                 )
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.1,
-                    maximum=20.0,
-                    step=0.1,
-                    value=0.0 if enable_lcm_arg else 5.0,
+                
+                with gr.Row():
+                    identitynet_strength_ratio = gr.Slider(
+                        label="Face Similarity",
+                        minimum=0.5,
+                        maximum=1.2,
+                        step=0.05,
+                        value=0.80,
+                    )
+                    adapter_strength_ratio = gr.Slider(
+                        label="Detail Quality",
+                        minimum=0.5,
+                        maximum=1.2,
+                        step=0.05,
+                        value=0.80,
+                    )
+                
+                enable_LCM = gr.Checkbox(
+                    label="Fast Generation Mode",
+                    value=False,
+                    info="Faster results with slightly lower quality"
                 )
-                seed = gr.Slider(
-                    label="Seed",
-                    minimum=0,
-                    maximum=MAX_SEED,
-                    step=1,
-                    value=42,
-                )
-                schedulers = [
-                    "DEISMultistepScheduler",
-                    "HeunDiscreteScheduler",
-                    "EulerDiscreteScheduler",
-                    "DPMSolverMultistepScheduler",
-                    "DPMSolverMultistepScheduler-Karras",
-                    "DPMSolverMultistepScheduler-Karras-SDE",
-                ]
-                scheduler = gr.Dropdown(
-                    label="Schedulers",
-                    choices=schedulers,
-                    value="EulerDiscreteScheduler",
-                )
-                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                enhance_face_region = gr.Checkbox(label="Enhance non-face region", value=True)
+
+            # Generate Button
+            submit = gr.Button("🚀 Generate Headshots", variant="primary", size="lg")
 
         with gr.Column(scale=1):
-            gallery = gr.Image(label="Generated Images")
-            usage_tips = gr.Markdown(
-                label="InstantID Usage Tips", value=tips, visible=False
+            # Results Section
+            gr.Markdown("### 🎉 Your Professional Headshots")
+            gallery = gr.Image(
+                label="Generated Headshot",
+                height=400,
+                show_download_button=True
             )
-
-        submit.click(
-            fn=remove_tips,
-            outputs=usage_tips,
-        ).then(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=generate_image,
-            inputs=[
-                face_file,
-                pose_file,
-                prompt,
-                negative_prompt,
-                style,
-                num_steps,
-                identitynet_strength_ratio,
-                adapter_strength_ratio,
-                #pose_strength,
-                canny_strength,
-                depth_strength,
-                controlnet_selection,
-                guidance_scale,
-                seed,
-                scheduler,
-                enable_LCM,
-                enhance_face_region,
-            ],
-            outputs=[gallery, usage_tips],
-        )
-
-        enable_LCM.input(
-            fn=toggle_lcm_ui,
-            inputs=[enable_LCM],
-            outputs=[num_steps, guidance_scale],
-            queue=False,
-        )
-
-    gr.Examples(
-        examples=get_example(),
-        inputs=[face_file, pose_file, prompt, style, negative_prompt],
-        fn=run_for_examples,
-        outputs=[gallery, usage_tips],
-        cache_examples=True,
+            
+            # Success Message
+            success_msg = gr.Markdown("""
+            <div style='background: #d4edda; padding: 15px; border-radius: 10px; border-left: 4px solid #28a745; margin-top: 20px;'>
+            <h4>✅ Success!</h4>
+            Your professional headshot is ready! Click the download button above to save your image.
+            </div>
+            """, visible=False)
+
+    # Hidden technical parameters (keep functionality but hide from users)
+    negative_prompt = gr.Textbox(
+        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",
+        visible=False
+    )
+    num_steps = gr.Slider(value=30, visible=False)
+    guidance_scale = gr.Slider(value=5.0, visible=False)
+    seed = gr.Slider(value=42, visible=False)
+    scheduler = gr.Dropdown(value="EulerDiscreteScheduler", visible=False)
+    randomize_seed = gr.Checkbox(value=True, visible=False)
+    enhance_face_region = gr.Checkbox(value=True, visible=False)
+    controlnet_selection = gr.CheckboxGroup(value=["depth"], visible=False)
+    canny_strength = gr.Slider(value=0.4, visible=False)
+    depth_strength = gr.Slider(value=0.4, visible=False)
+
+    def show_success():
+        return gr.update(visible=True)
+
+    submit.click(
+        fn=generate_image,
+        inputs=[
+            face_file,
+            gr.update(visible=False),  # pose_file hidden
+            prompt,
+            negative_prompt,
+            style,
+            num_steps,
+            identitynet_strength_ratio,
+            adapter_strength_ratio,
+            canny_strength,
+            depth_strength,
+            controlnet_selection,
+            guidance_scale,
+            seed,
+            scheduler,
+            enable_LCM,
+            enhance_face_region,
+        ],
+        outputs=[gallery, success_msg]
+    ).then(
+        fn=show_success,
+        outputs=success_msg
     )
 
-    gr.Markdown(article)
+    enable_LCM.input(
+        fn=toggle_lcm_ui,
+        inputs=[enable_LCM],
+        outputs=[num_steps, guidance_scale],
+        queue=False,
+    )
 
 demo.queue(api_open=False)
-demo.launch()
+demo.launch(share=True)