update

app.py

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+
+import os
+os.system("pip install mmcv-full==1.7.0")
+os.system("pip install tensorflow")
+os.system("pip install modelscope")
+
+import cv2
+import gradio as gr
+import numpy as np
+import PIL.Image as Image
+import torch
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.utils.cv.image_utils import draw_face_detection_result
+from modelscope.preprocessors.image import LoadImage
+
+import warnings
+
+warnings.filterwarnings("ignore")
+
+
+# 定义推理函数
+def detect_faces(img_pil, model_name):
+    # 定义模型
+    face_detection = pipeline(task=Tasks.face_detection, model='damo/cv_ddsar_face-detection_iclr23-damofd')
+    img_dir = "input_img.jpg"
+    img_pil.save(img_dir)
+    # 进行人脸检测
+    result = face_detection(img_dir)
+    # 可视化结果
+    img_cv = draw_face_detection_result(img_dir, result)
+    # 将结果转换为 Gradio 的输出格式
+    img_out_pil = Image.fromarray(cv2.cvtColor(img_cv, cv2.COLOR_BGR2RGB))
+    return img_out_pil
+
+def download_test_image():
+    # Images
+    torch.hub.download_url_to_file(
+        'https://user-images.githubusercontent.com/59380685/269160118-91a4a758-1ee0-47a3-a873-28bfd8c24a7f.jpg',
+        'faces.jpg')
+    torch.hub.download_url_to_file(
+        'https://user-images.githubusercontent.com/59380685/269160674-bbf4af8b-a5f1-4754-a272-fd7d278050a3.jpg',
+        '000000000110.jpg')
+
+
+easyface_model_list = ['damo/cv_ddsar_face-detection_iclr23-damofd',
+                       'damo/cv_resnet101_face-detection_cvpr22papermogface',
+                       'damo/cv_resnet50_face-detection_retinaface',
+                       'damo/cv_manual_face-detection_mtcnn']
+
+if __name__ == '__main__':
+    download_test_image()
+    # 定义输入和输出
+    inputs = gr.inputs.Image(type='pil', label="input")
+    model_name = gr.inputs.Dropdown(choices=easyface_model_list, label="model list",
+                                    default="damo/cv_ddsar_face-detection_iclr23-damofd")
+    example = [["faces.jpg", "damo/cv_ddsar_face-detection_iclr23-damofd"],
+               ["000000000110.jpg", "damo/cv_manual_face-detection_mtcnn"]]
+    outputs = gr.outputs.Image(type='pil', label="output")
+    title = "EasyFace Web Demo"
+    description = "EasyFace旨在快速选型/了解/对比/体验人脸相关sota模型，依托于Modelscope开发库和Pytorch框架"
+    # 启动 Gradio 应用
+    gr.Interface(fn=detect_faces,
+                 inputs=[inputs, model_name],
+                 outputs=outputs, title=title,
+                 examples=example,
+                 description=description).launch()

requirements.txt

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+git+https://github.com/facebookresearch/[email protected]#egg=detectron2
+ultralytics~=8.0.169
+wget~=3.2
+opencv-python~=4.6.0.66
+torch
+torchvision
+tensorflow
+numpy~=1.23.0
+pillow~=9.4.0
+gradio~=3.42.0
+pyyaml~=6.0
+wandb~=0.13.11
+tqdm~=4.65.0
+matplotlib~=3.7.1
+pandas~=2.0.0
+seaborn~=0.12.2
+requests~=2.31.0
+psutil~=5.9.4
+thop~=0.1.1-2209072238
+timm~=0.9.2
+super-gradients~=3.2.0
+openmim