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from pdb import set_trace as bb |
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import numpy as np |
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from PIL import Image, ImageOps, ImageEnhance |
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def grab( data, *fields ): |
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''' Called to extract fields from a dictionary |
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''' |
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if isinstance(data, dict): |
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res = [] |
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for f in fields: |
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res.append( data[f] ) |
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return res[0] if len(fields) == 1 else tuple(res) |
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else: |
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assert fields == ('img',) and isinstance(data, (np.ndarray, Image.Image)), \ |
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f"data should be an image, not {type(data)}!" |
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return data |
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def update( data, **fields): |
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''' Called to update the img_and_label |
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''' |
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if isinstance( data, dict): |
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if 'homography' in fields and 'homography' in data: |
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data['homography'] = fields.pop('homography') @ data['homography'] |
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data.update(fields) |
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if 'img' in fields: |
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data['imsize'] = data['img'].size |
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return data |
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else: |
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return fields['img'] |
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def rand_log_uniform(rng, a, b): |
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return np.exp(rng.uniform(np.log(a),np.log(b))) |
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def translate(tx, ty): |
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return np.float32(((1,0,tx),(0,1,ty,),(0,0,1))) |
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def rotate(angle): |
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return np.float32(((np.cos(angle),-np.sin(angle),0),(np.sin(angle),np.cos(angle),0),(0,0,1))) |
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def is_pil_image(img): |
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return isinstance(img, Image.Image) |
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def homography_from_4pts(pts_cur, pts_new): |
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"pts_cur and pts_new = 4x2 point array, in [(x,y),...] format" |
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matrix = [] |
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for p1, p2 in zip(pts_new, pts_cur): |
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matrix.append([p1[0], p1[1], 1, 0, 0, 0, -p2[0] * p1[0], -p2[0] * p1[1]]) |
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matrix.append([0, 0, 0, p1[0], p1[1], 1, -p2[1] * p1[0], -p2[1] * p1[1]]) |
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A = np.matrix(matrix, dtype=np.float) |
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B = np.array(pts_cur).reshape(8) |
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homography = np.dot(np.linalg.pinv(A), B) |
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homography = tuple(np.array(homography).reshape(8)) |
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return homography |
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