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import numpy as np |
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import cv2 |
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from face_detect.core import randomex |
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def gen_warp_params (w, flip=False, rotation_range=[-10,10], scale_range=[-0.5, 0.5], tx_range=[-0.05, 0.05], ty_range=[-0.05, 0.05], rnd_state=None ): |
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if rnd_state is None: |
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rnd_state = np.random |
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rw = None |
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if w < 64: |
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rw = w |
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w = 64 |
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rotation = rnd_state.uniform( rotation_range[0], rotation_range[1] ) |
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scale = rnd_state.uniform(1 +scale_range[0], 1 +scale_range[1]) |
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tx = rnd_state.uniform( tx_range[0], tx_range[1] ) |
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ty = rnd_state.uniform( ty_range[0], ty_range[1] ) |
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p_flip = flip and rnd_state.randint(10) < 4 |
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cell_size = [ w // (2**i) for i in range(1,4) ] [ rnd_state.randint(3) ] |
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cell_count = w // cell_size + 1 |
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grid_points = np.linspace( 0, w, cell_count) |
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mapx = np.broadcast_to(grid_points, (cell_count, cell_count)).copy() |
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mapy = mapx.T |
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mapx[1:-1,1:-1] = mapx[1:-1,1:-1] + randomex.random_normal( size=(cell_count-2, cell_count-2) )*(cell_size*0.24) |
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mapy[1:-1,1:-1] = mapy[1:-1,1:-1] + randomex.random_normal( size=(cell_count-2, cell_count-2) )*(cell_size*0.24) |
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half_cell_size = cell_size // 2 |
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mapx = cv2.resize(mapx, (w+cell_size,)*2 )[half_cell_size:-half_cell_size,half_cell_size:-half_cell_size].astype(np.float32) |
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mapy = cv2.resize(mapy, (w+cell_size,)*2 )[half_cell_size:-half_cell_size,half_cell_size:-half_cell_size].astype(np.float32) |
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random_transform_mat = cv2.getRotationMatrix2D((w // 2, w // 2), rotation, scale) |
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random_transform_mat[:, 2] += (tx*w, ty*w) |
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params = dict() |
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params['mapx'] = mapx |
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params['mapy'] = mapy |
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params['rmat'] = random_transform_mat |
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u_mat = random_transform_mat.copy() |
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u_mat[:,2] /= w |
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params['umat'] = u_mat |
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params['w'] = w |
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params['rw'] = rw |
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params['flip'] = p_flip |
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return params |
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def warp_by_params (params, img, can_warp, can_transform, can_flip, border_replicate, cv2_inter=cv2.INTER_CUBIC): |
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rw = params['rw'] |
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if (can_warp or can_transform) and rw is not None: |
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img = cv2.resize(img, (64,64), interpolation=cv2_inter) |
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if can_warp: |
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img = cv2.remap(img, params['mapx'], params['mapy'], cv2_inter ) |
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if can_transform: |
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img = cv2.warpAffine( img, params['rmat'], (params['w'], params['w']), borderMode=(cv2.BORDER_REPLICATE if border_replicate else cv2.BORDER_CONSTANT), flags=cv2_inter ) |
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if (can_warp or can_transform) and rw is not None: |
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img = cv2.resize(img, (rw,rw), interpolation=cv2_inter) |
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if len(img.shape) == 2: |
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img = img[...,None] |
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if can_flip and params['flip']: |
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img = img[:,::-1,...] |
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return img |
