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Browse files- README.md +1 -1
- app.py +75 -0
- core.bin +3 -0
- imgs/11.jpg +0 -0
- imgs/13.jpg +0 -0
- mic.bin +3 -0
- requirements.txt +11 -0
- z_app_factory.so +0 -0
README.md
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---
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title: Detect Living Face
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emoji:
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colorFrom: pink
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colorTo: indigo
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sdk: gradio
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---
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title: Detect Living Face
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emoji: 🤖
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colorFrom: pink
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colorTo: indigo
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sdk: gradio
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app.py
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import cv2
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import gradio as gr
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import io
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import numpy as np
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from z_app_factory import get_app
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thickness = 3
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lineType = 8
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font = cv2.FONT_HERSHEY_SIMPLEX
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def inference(image):
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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dic_res = get_app(image)
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code = dic_res["code"]
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data = dic_res["data"]
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msg = "aaa"
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if code == 401:
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msg = "Not RGB three channel picture"
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elif code == 402:
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msg = "Pixels less than 32 * 32"
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elif code == 403:
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msg = "Pixels greater than 4096 * 4096"
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elif code == 404:
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msg = "Files greater than 5MB"
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elif code == 405:
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msg = "System error, please contact\n the server for troubleshooting"
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import numpy as np
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img_out = np.zeros((500, 600, 3), dtype=np.uint8)
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if code!=200:
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cv2.putText(img_out, msg, (20, 200), font, 1, (0, 255, 0), 2)
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return img_out
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if code==200 and not data:
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cv2.putText(img_out, "no face detected", (20, 200), font, 1, (0, 255, 0), 2)
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return img_out
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lst_bbox = data['bbox']
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lst_score = data['score']
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for idx, image_bbox in enumerate(lst_bbox):
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score = lst_score[idx]
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cv2.rectangle(
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image,
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(image_bbox[0], image_bbox[1]),
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(image_bbox[0] + image_bbox[2], image_bbox[1] + image_bbox[3]),
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(0, int(255 * score), 0), 2)
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cv2.putText(
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image,
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str(score)[:4],
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(image_bbox[0], image_bbox[1] - 5),
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cv2.FONT_HERSHEY_SIMPLEX, 1.5 * image.shape[0] / 1024, (0, int(255 * score), 0), 2)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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return image
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title = "Face Keypoint 3d"
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description = "demo for Face Keypoint 3d. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://www.yuque.com/itmorn/ability/face_keypoint_3d' target='_blank'>Project Documents</a> | <a href='https://www.bilibili.com/video/BV1GD4y1y77z' target='_blank'>Video Demo</a></p>"
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gr.Interface(
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inference,
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[gr.inputs.Image(label="Input")],
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gr.outputs.Image(type="pil", label="Output"),
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title=title,
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description=description,
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article=article,
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examples=[
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["imgs/11.jpg"],
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["imgs/13.jpg"],
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]).launch(debug=True)
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core.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:722b367e4ceb510545a47b2e514093fc04a82c4d8df0f535c417c1ddfa420a46
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size 25802730
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imgs/11.jpg
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imgs/13.jpg
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mic.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d6d4f42c2272406ddb5c278a8548269437f61022e4bacc709cbbccc758a37085
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size 1510312
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requirements.txt
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pyarmor
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opencv-python
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onnxruntime-gpu
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onnx
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py7zr
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onnx
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tqdm
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scikit-image
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fs
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flask
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torch
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z_app_factory.so
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Binary file (664 kB). View file
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