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| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| import torch | |
| import kornia as K | |
| from kornia.core import Tensor | |
| from kornia.contrib import FaceDetector, FaceDetectorResult, FaceKeypoint | |
| def draw_keypoint(img: np.ndarray, det: FaceDetectorResult, kpt_type: FaceKeypoint) -> np.ndarray: | |
| kpt = det.get_keypoint(kpt_type).int().tolist() | |
| return cv2.circle(img, kpt, 2, (255, 0, 0), 2) | |
| def detect(img_raw): | |
| # preprocess | |
| if img_raw is not None and len(img_raw.shape) == 3: | |
| img = K.image_to_tensor(img_raw, keepdim=False) | |
| img = K.color.bgr_to_rgb(img.float()) | |
| # create the detector and find the faces ! | |
| face_detection = FaceDetector() | |
| with torch.no_grad(): | |
| dets = face_detection(img) | |
| dets = [FaceDetectorResult(o) for o in dets[0]] | |
| img_vis = img_raw.copy() | |
| vis_threshold = 0.8 | |
| for b in dets: | |
| if b.score < vis_threshold: | |
| continue | |
| # Draw face bounding box | |
| img_vis = cv2.rectangle(img_vis, b.top_left.int().tolist(), b.bottom_right.int().tolist(), (0, 255, 0), 4) | |
| # Draw Keypoints | |
| img_vis = draw_keypoint(img_vis, b, FaceKeypoint.EYE_LEFT) | |
| img_vis = draw_keypoint(img_vis, b, FaceKeypoint.EYE_RIGHT) | |
| img_vis = draw_keypoint(img_vis, b, FaceKeypoint.NOSE) | |
| img_vis = draw_keypoint(img_vis, b, FaceKeypoint.MOUTH_LEFT) | |
| img_vis = draw_keypoint(img_vis, b, FaceKeypoint.MOUTH_RIGHT) | |
| return img_vis | |
| title = "Kornia Face Detection" | |
| description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Face Detection.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them</p>" | |
| article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia.readthedocs.io/en/latest/applications/face_detection.html' target='_blank'>Kornia Face Detection Tutorial</a></p>" | |
| examples = ['sample.jpg'] | |
| face = gr.Interface( | |
| detect, | |
| gr.inputs.Image(type="numpy"), | |
| gr.Image(type="pil", interactive=False), | |
| examples=examples, | |
| title=title, | |
| description=description, | |
| article=article, | |
| live=True, | |
| allow_flagging="never" | |
| ) | |
| face.launch() | |