隐藏huggingface上的gradio UI，当后端服务启用

app.py

@@ -68,44 +68,44 @@ def remove_tips():
     return gr.update(visible=False)
 
 
-def get_example():
-    case = [
-        [
-            "./examples/yann-lecun_resize.jpg",
-            "a man",
-            "Snow",
-            "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
-        ],
-        [
-            "./examples/musk_resize.jpeg",
-            "a man",
-            "Mars",
-            "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
-        ],
-        [
-            "./examples/sam_resize.png",
-            "a man",
-            "Jungle",
-            "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, gree",
-        ],
-        [
-            "./examples/schmidhuber_resize.png",
-            "a man",
-            "Neon",
-            "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
-        ],
-        [
-            "./examples/kaifu_resize.png",
-            "a man",
-            "Vibrant Color",
-            "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
-        ],
-    ]
-    return case
-
-
-def run_for_examples(face_file, prompt, style, negative_prompt):
-    return generate_image(face_file, None, prompt, negative_prompt, style, True, 30, 0.8, 0.8, 5, 42)
+# def get_example():
+#     case = [
+#         [
+#             "./examples/yann-lecun_resize.jpg",
+#             "a man",
+#             "Snow",
+#             "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
+#         ],
+#         [
+#             "./examples/musk_resize.jpeg",
+#             "a man",
+#             "Mars",
+#             "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
+#         ],
+#         [
+#             "./examples/sam_resize.png",
+#             "a man",
+#             "Jungle",
+#             "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, gree",
+#         ],
+#         [
+#             "./examples/schmidhuber_resize.png",
+#             "a man",
+#             "Neon",
+#             "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
+#         ],
+#         [
+#             "./examples/kaifu_resize.png",
+#             "a man",
+#             "Vibrant Color",
+#             "(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, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
+#         ],
+#     ]
+#     return case
+
+
+# def run_for_examples(face_file, prompt, style, negative_prompt):
+#     return generate_image(face_file, None, prompt, negative_prompt, style, True, 30, 0.8, 0.8, 5, 42)
 
 
 def convert_from_cv2_to_image(img: np.ndarray) -> Image:
@@ -240,6 +240,7 @@ def generate_image(
 
         width, height = face_kps.size
 
+    # 面部增强
     if enhance_face_region:
         control_mask = np.zeros([height, width, 3])
         x1, y1, x2, y2 = face_info["bbox"]
@@ -251,8 +252,8 @@ def generate_image(
 
     generator = torch.Generator(device=device).manual_seed(seed)
 
-    print("Start inference...")
-    print(f"[Debug] Prompt: {prompt}, \n[Debug] Neg Prompt: {negative_prompt}")
+    # print("Start inference...")
+    # print(f"[Debug] Prompt: {prompt}, \n[Debug] Neg Prompt: {negative_prompt}")
 
     pipe.set_ip_adapter_scale(adapter_strength_ratio)
     images = pipe(
@@ -272,169 +273,169 @@ def generate_image(
     return images[0], gr.update(visible=True)
 
 
-### Description
-title = r"""
-<h1 align="center">InstantID: Zero-shot Identity-Preserving Generation in Seconds</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>
-
-How to use:<br>
-1. Upload a person image. For multiple person images, we will only detect the biggest face. Make sure face is not too small and not significantly blocked or blurred.
-2. (Optionally) upload another person image as reference pose. If not uploaded, we will use the first person image to extract landmarks. If you use a cropped face at step1, it is recommeneded to upload it to extract a new pose.
-3. Enter a text prompt as done in normal text-to-image models.
-4. Click the <b>Submit</b> button to start customizing.
-5. Share your customizd photo with your friends, 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>[email protected]</b>.
-"""
-
-tips = r"""
-### Usage tips of InstantID
-1. If you're unsatisfied with the similarity, increase the weight of controlnet_conditioning_scale (IdentityNet) and ip_adapter_scale (Adapter).
-2. If the generated image is over-saturated, decrease the ip_adapter_scale. If not work, decrease controlnet_conditioning_scale.
-3. If text control is not as expected, decrease ip_adapter_scale.
-4. Find a good base model always makes a difference.
-"""
-
-css = """
-.gradio-container {width: 85% !important}
-"""
-with gr.Blocks(css=css) as demo:
-    # description
-    gr.Markdown(title)
-    gr.Markdown(description)
-
-    with gr.Row():
-        with gr.Column():
-            # upload face image
-            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)", type="filepath")
-
-            # prompt
-            prompt = gr.Textbox(
-                label="Prompt",
-                info="Give simple prompt is enough to achieve good face fedility",
-                placeholder="A photo of a person",
-                value="",
-            )
-
-            submit = gr.Button("Submit", variant="primary")
-
-            style = gr.Dropdown(label="Style template", choices=STYLE_NAMES, value=DEFAULT_STYLE_NAME)
-
-            # strength
-            identitynet_strength_ratio = gr.Slider(
-                label="IdentityNet strength (for fedility)",
-                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(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, nudity,naked, bikini, skimpy, scanty, bare skin, lingerie, swimsuit, exposed, see-through, 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=20,
-                    maximum=100,
-                    step=1,
-                    value=30,
-                )
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.1,
-                    maximum=10.0,
-                    step=0.1,
-                    value=5,
-                )
-                seed = gr.Slider(
-                    label="Seed",
-                    minimum=0,
-                    maximum=MAX_SEED,
-                    step=1,
-                    value=42,
-                )
-                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                enhance_face_region = gr.Checkbox(label="Enhance non-face region", value=True)
-
-        with gr.Column():
-            output_image = gr.Image(label="Generated Image")
-            usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
-
-        submit.click(
-            fn=remove_tips,
-            outputs=usage_tips,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=check_input_image,
-            inputs=face_file,
-            queue=False,
-            api_name=False,
-        ).success(
-            fn=generate_image,
-            inputs=[
-                face_file,
-                pose_file,
-                prompt,
-                negative_prompt,
-                style,
-                enhance_face_region,
-                num_steps,
-                identitynet_strength_ratio,
-                adapter_strength_ratio,
-                guidance_scale,
-                seed,
-            ],
-            outputs=[output_image, usage_tips],
-        )
-
-    gr.Examples(
-        examples=get_example(),
-        inputs=[face_file, prompt, style, negative_prompt],
-        outputs=[output_image, usage_tips],
-        fn=run_for_examples,
-        cache_examples=True,
-    )
-
-    gr.Markdown(article)
+# ### Description
+# title = r"""
+# <h1 align="center">InstantID: Zero-shot Identity-Preserving Generation in Seconds</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>
+
+# How to use:<br>
+# 1. Upload a person image. For multiple person images, we will only detect the biggest face. Make sure face is not too small and not significantly blocked or blurred.
+# 2. (Optionally) upload another person image as reference pose. If not uploaded, we will use the first person image to extract landmarks. If you use a cropped face at step1, it is recommeneded to upload it to extract a new pose.
+# 3. Enter a text prompt as done in normal text-to-image models.
+# 4. Click the <b>Submit</b> button to start customizing.
+# 5. Share your customizd photo with your friends, 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>[email protected]</b>.
+# """
+
+# tips = r"""
+# ### Usage tips of InstantID
+# 1. If you're unsatisfied with the similarity, increase the weight of controlnet_conditioning_scale (IdentityNet) and ip_adapter_scale (Adapter).
+# 2. If the generated image is over-saturated, decrease the ip_adapter_scale. If not work, decrease controlnet_conditioning_scale.
+# 3. If text control is not as expected, decrease ip_adapter_scale.
+# 4. Find a good base model always makes a difference.
+# """
+
+# css = """
+# .gradio-container {width: 85% !important}
+# """
+# with gr.Blocks(css=css) as demo:
+#     # description
+#     gr.Markdown(title)
+#     gr.Markdown(description)
+
+#     with gr.Row():
+#         with gr.Column():
+#             # upload face image
+#             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)", type="filepath")
+
+#             # prompt
+#             prompt = gr.Textbox(
+#                 label="Prompt",
+#                 info="Give simple prompt is enough to achieve good face fedility",
+#                 placeholder="A photo of a person",
+#                 value="",
+#             )
+
+#             submit = gr.Button("Submit", variant="primary")
+
+#             style = gr.Dropdown(label="Style template", choices=STYLE_NAMES, value=DEFAULT_STYLE_NAME)
+
+#             # strength
+#             identitynet_strength_ratio = gr.Slider(
+#                 label="IdentityNet strength (for fedility)",
+#                 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(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, nudity,naked, bikini, skimpy, scanty, bare skin, lingerie, swimsuit, exposed, see-through, 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=20,
+#                     maximum=100,
+#                     step=1,
+#                     value=30,
+#                 )
+#                 guidance_scale = gr.Slider(
+#                     label="Guidance scale",
+#                     minimum=0.1,
+#                     maximum=10.0,
+#                     step=0.1,
+#                     value=5,
+#                 )
+#                 seed = gr.Slider(
+#                     label="Seed",
+#                     minimum=0,
+#                     maximum=MAX_SEED,
+#                     step=1,
+#                     value=42,
+#                 )
+#                 randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+#                 enhance_face_region = gr.Checkbox(label="Enhance non-face region", value=True)
+
+#         with gr.Column():
+#             output_image = gr.Image(label="Generated Image")
+#             usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
+
+#         submit.click(
+#             fn=remove_tips,
+#             outputs=usage_tips,
+#             queue=False,
+#             api_name=False,
+#         ).then(
+#             fn=randomize_seed_fn,
+#             inputs=[seed, randomize_seed],
+#             outputs=seed,
+#             queue=False,
+#             api_name=False,
+#         ).then(
+#             fn=check_input_image,
+#             inputs=face_file,
+#             queue=False,
+#             api_name=False,
+#         ).success(
+#             fn=generate_image,
+#             inputs=[
+#                 face_file,
+#                 pose_file,
+#                 prompt,
+#                 negative_prompt,
+#                 style,
+#                 enhance_face_region,
+#                 num_steps,
+#                 identitynet_strength_ratio,
+#                 adapter_strength_ratio,
+#                 guidance_scale,
+#                 seed,
+#             ],
+#             outputs=[output_image, usage_tips],
+#         )
+
+    # gr.Examples(
+    #     examples=get_example(),
+    #     inputs=[face_file, prompt, style, negative_prompt],
+    #     outputs=[output_image, usage_tips],
+    #     fn=run_for_examples,
+    #     cache_examples=True,
+    # )
+
+    # gr.Markdown(article)
 
 demo.queue(api_open=False)
 demo.launch()