kopia lustrzana https://github.com/Shawn-Shan/fawkes
81 wiersze
2.7 KiB
Python
81 wiersze
2.7 KiB
Python
import numpy as np
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from mtcnn import MTCNN
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def to_rgb(img):
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w, h = img.shape
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ret = np.empty((w, h, 3), dtype=np.uint8)
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ret[:, :, 0] = ret[:, :, 1] = ret[:, :, 2] = img
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return ret
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def aligner():
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return MTCNN(min_face_size=30)
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def align(orig_img, aligner):
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""" run MTCNN face detector """
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if orig_img.ndim < 2:
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return None
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if orig_img.ndim == 2:
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orig_img = to_rgb(orig_img)
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orig_img = orig_img[:, :, 0:3]
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detect_results = aligner.detect_faces(orig_img)
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cropped_arr = []
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bounding_boxes_arr = []
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for dic in detect_results:
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if dic['confidence'] < 0.9:
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continue
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x, y, width, height = dic['box']
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if width < 30 or height < 30:
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continue
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bb = [y, x, y + height, x + width]
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cropped = orig_img[bb[0]:bb[2], bb[1]:bb[3], :]
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cropped_arr.append(np.copy(cropped))
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bounding_boxes_arr.append(bb)
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return cropped_arr, bounding_boxes_arr
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# if nrof_faces > 0:
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# det = bounding_boxes[0]['box']
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# det_arr = []
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# img_size = np.asarray(orig_img.shape)[0:2]
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# if nrof_faces > 1:
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# margin = margin / 1.5
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# if detect_multiple_faces:
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# for i in range(nrof_faces):
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# det_arr.append(np.squeeze(bounding_boxes[i]['box']))
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# else:
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# bounding_box_size = (det[1] + det[3])
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# img_center = img_size / 2
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# offsets = np.vstack([(det[0] + det[2]) / 2 - img_center[1],
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# (det[1] + det[3]) / 2 - img_center[0]])
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# offset_dist_squared = np.sum(np.power(offsets, 2.0), 0)
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# index = np.argmax(bounding_box_size - offset_dist_squared * 2.0) # some extra weight on the centering
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# det_arr.append(det[index, :])
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# else:
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# det_arr.append(np.squeeze(det))
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#
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# cropped_arr = []
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# bounding_boxes_arr = []
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# for i, det in enumerate(det_arr):
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# det = np.squeeze(det)
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# bb = np.zeros(4, dtype=np.int32)
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# # add in margin
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# marg1 = int((det[2] - det[0]) * margin)
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# marg2 = int((det[3] - det[1]) * margin)
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#
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# bb[0] = max(det[0] - marg1 / 2, 0)
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# bb[1] = max(det[1] - marg2 / 2, 0)
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# bb[2] = min(det[0] + det[2] + marg1 / 2, img_size[0])
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# bb[3] = min(det[1] + det[3] + marg2 / 2, img_size[1])
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# cropped = orig_img[bb[0]:bb[2], bb[1]: bb[3], :]
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# cropped_arr.append(cropped)
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# bounding_boxes_arr.append([bb[0], bb[1], bb[2], bb[3]])
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# return cropped_arr, bounding_boxes_arr
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# else:
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# return None
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