feat: Dockerfile改进，显示界面改成标题和提示为中文、可生成公开链接的方式。

Dockerfile

@@ -12,7 +12,7 @@ RUN pip install -r gradio_demo/requirements.txt && \
 # Prod  #
 #########
 FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.2.0-python3.10-cuda12.1-ubuntu22.04
+RUN apt-get update && apt-get install -y libglib2.0-0 libgl1-mesa-glx
 COPY --from=base /opt/conda/lib/python3.10/site-packages /opt/conda/lib/python3.10/site-packages
 COPY --from=base /root/instantid/InstantID /root/InstantID
 COPY --from=base /root/instantid/启动器.ipynb /root/instantid/run.sh /root/
-# RUN apt-get update && apt-get install -y libglib2.0-0 libgl1-mesa-glx
\ No newline at end of file

InstantID/gradio_demo/app.py

 import sys
+
 sys.path.append('./')
 
 from typing import Tuple
@@ -48,8 +49,8 @@ controlnet_path = f'./checkpoints/ControlNetModel'
 # Load pipeline
 controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=dtype)
 
-def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=False):
 
+def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=False):
     if pretrained_model_name_or_path.endswith(
             ".ckpt"
     ) or pretrained_model_name_or_path.endswith(".safetensors"):
@@ -92,6 +93,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
     # load and disable LCM
     pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
     pipe.disable_lora()
+
     def toggle_lcm_ui(value):
         if value:
             return (
@@ -156,7 +158,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
     def convert_from_image_to_cv2(img: Image) -> np.ndarray:
         return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
 
-    def draw_kps(image_pil, kps, color_list=[(255,0,0), (0,255,0), (0,0,255), (255,255,0), (255,0,255)]):
+    def draw_kps(image_pil, kps, color_list=[(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 255, 0), (255, 0, 255)]):
         stickwidth = 4
         limbSeq = np.array([[0, 2], [1, 2], [3, 2], [4, 2]])
         kps = np.array(kps)
@@ -172,7 +174,8 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
             y = kps[index][:, 1]
             length = ((x[0] - x[1]) ** 2 + (y[0] - y[1]) ** 2) ** 0.5
             angle = math.degrees(math.atan2(y[0] - y[1], x[0] - x[1]))
-            polygon = cv2.ellipse2Poly((int(np.mean(x)), int(np.mean(y))), (int(length / 2), stickwidth), int(angle), 0, 360, 1)
+            polygon = cv2.ellipse2Poly((int(np.mean(x)), int(np.mean(y))), (int(length / 2), stickwidth), int(angle), 0,
+                                       360, 1)
             out_img = cv2.fillConvexPoly(out_img.copy(), polygon, color)
         out_img = (out_img * 0.6).astype(np.uint8)
 
@@ -192,9 +195,9 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
             w_resize_new, h_resize_new = size
         else:
             ratio = min_side / min(h, w)
-                w, h = round(ratio*w), round(ratio*h)
+            w, h = round(ratio * w), round(ratio * h)
             ratio = max_side / max(h, w)
-                input_image = input_image.resize([round(ratio*w), round(ratio*h)], mode)
+            input_image = input_image.resize([round(ratio * w), round(ratio * h)], mode)
             w_resize_new = (round(ratio * w) // base_pixel_number) * base_pixel_number
             h_resize_new = (round(ratio * h) // base_pixel_number) * base_pixel_number
         input_image = input_image.resize([w_resize_new, h_resize_new], mode)
@@ -203,7 +206,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
             res = np.ones([max_side, max_side, 3], dtype=np.uint8) * 255
             offset_x = (max_side - w_resize_new) // 2
             offset_y = (max_side - h_resize_new) // 2
-                res[offset_y:offset_y+h_resize_new, offset_x:offset_x+w_resize_new] = np.array(input_image)
+            res[offset_y:offset_y + h_resize_new, offset_x:offset_x + w_resize_new] = np.array(input_image)
             input_image = Image.fromarray(res)
         return input_image
 
@@ -211,7 +214,9 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
         return p.replace("{prompt}", positive), n + ' ' + negative
 
-    def generate_image(face_image_path, pose_image_path, prompt, negative_prompt, style_name, num_steps, identitynet_strength_ratio, adapter_strength_ratio, guidance_scale, seed, enable_LCM, enhance_face_region, progress=gr.Progress(track_tqdm=True)):
+    def generate_image(face_image_path, pose_image_path, prompt, negative_prompt, style_name, num_steps,
+                       identitynet_strength_ratio, adapter_strength_ratio, guidance_scale, seed, enable_LCM,
+                       enhance_face_region, progress=gr.Progress(track_tqdm=True)):
         if enable_LCM:
             pipe.enable_lora()
             pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
@@ -239,7 +244,8 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
         if len(face_info) == 0:
             raise gr.Error(f"Cannot find any face in the image! Please upload another person image")
 
-        face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*(x['bbox'][3]-x['bbox'][1]))[-1]  # only use the maximum face
+        face_info = sorted(face_info, key=lambda x: (x['bbox'][2] - x['bbox'][0]) * (x['bbox'][3] - x['bbox'][1]))[
+            -1]  # only use the maximum face
         face_emb = face_info['embedding']
         face_kps = draw_kps(convert_from_cv2_to_image(face_image_cv2), face_info['kps'])
 
@@ -291,18 +297,17 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
 
     ### Description
     title = r"""
-    <h1 align="center">InstantID: Zero-shot Identity-Preserving Generation in Seconds</h1>
+    <h1 align="center">InstantID: 1张照片，无需训练，秒级生成个人写真</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 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. Enter a text prompt, as done in normal text-to-image models.
-    4. Click the <b>Submit</b> button to begin customization.
-    5. Share your customized photo with your friends and enjoy! 😊
+    <b>官方Gradio demo</b> for <a href='https://github.com/InstantID/InstantID' target='_blank'><b>InstantID: 1张照片，无需训练，秒级生成个人写真</b></a>.<br>
+    用户指南:<br>
+    1. 上传人物图片。 对于多人图像，我们只会检测最大的脸部。 确保脸部不要太小，并且没有明显遮挡或模糊。
+    2. （可选）上传另一个人的图像作为参考姿势。 如果没有上传，我们将使用第一张图像来提取姿势。 如果您在步骤1中使用了裁剪后的脸部，建议上传它以提取新的姿势。
+    3. （可选）输入文本prompt提示词，就像所有文生图应用中所做的那样.
+    4. 点击 <b>Submit</b> 按钮开始定制.
+    5. 分享美图给你的好友吧, enjoy😊!
     """
 
     article = r"""
@@ -342,7 +347,6 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
 
         with gr.Row():
             with gr.Column():
-                
                 # upload face image
                 face_file = gr.Image(label="Upload a photo of your face", type="filepath")
 
@@ -411,7 +415,7 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
 
             with gr.Column():
                 gallery = gr.Image(label="Generated Images")
-                usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips ,visible=False)
+                usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
 
             submit.click(
                 fn=remove_tips,
@@ -424,7 +428,8 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
                 api_name=False,
             ).then(
                 fn=generate_image,
-                inputs=[face_file, pose_file, prompt, negative_prompt, style, num_steps, identitynet_strength_ratio, adapter_strength_ratio, guidance_scale, seed, enable_LCM, enhance_face_region],
+                inputs=[face_file, pose_file, prompt, negative_prompt, style, num_steps, identitynet_strength_ratio,
+                        adapter_strength_ratio, guidance_scale, seed, enable_LCM, enhance_face_region],
                 outputs=[gallery, usage_tips]
             )
 
@@ -441,7 +446,8 @@ def main(pretrained_model_name_or_path="wangqixun/YamerMIX_v8", enable_lcm_arg=F
 
         gr.Markdown(article)
 
-    demo.launch(server_name='0.0.0.0')
+    demo.launch(server_name='0.0.0.0', share=True)
+
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()