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import numpy as np |
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import math |
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from SiamMask.utils.bbox_helper import center2corner, corner2center |
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class Anchors: |
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def __init__(self, cfg): |
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self.stride = 8 |
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self.ratios = [0.33, 0.5, 1, 2, 3] |
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self.scales = [8] |
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self.round_dight = 0 |
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self.image_center = 0 |
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self.size = 0 |
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self.anchor_density = 1 |
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self.__dict__.update(cfg) |
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self.anchor_num = len(self.scales) * len(self.ratios) * (self.anchor_density**2) |
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self.anchors = None |
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self.all_anchors = None |
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self.generate_anchors() |
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def generate_anchors(self): |
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self.anchors = np.zeros((self.anchor_num, 4), dtype=np.float32) |
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size = self.stride * self.stride |
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count = 0 |
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anchors_offset = self.stride / self.anchor_density |
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anchors_offset = np.arange(self.anchor_density)*anchors_offset |
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anchors_offset = anchors_offset - np.mean(anchors_offset) |
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x_offsets, y_offsets = np.meshgrid(anchors_offset, anchors_offset) |
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for x_offset, y_offset in zip(x_offsets.flatten(), y_offsets.flatten()): |
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for r in self.ratios: |
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if self.round_dight > 0: |
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ws = round(math.sqrt(size*1. / r), self.round_dight) |
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hs = round(ws * r, self.round_dight) |
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else: |
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ws = int(math.sqrt(size*1. / r)) |
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hs = int(ws * r) |
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for s in self.scales: |
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w = ws * s |
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h = hs * s |
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self.anchors[count][:] = [-w*0.5+x_offset, -h*0.5+y_offset, w*0.5+x_offset, h*0.5+y_offset][:] |
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count += 1 |
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def generate_all_anchors(self, im_c, size): |
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if self.image_center == im_c and self.size == size: |
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return False |
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self.image_center = im_c |
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self.size = size |
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a0x = im_c - size // 2 * self.stride |
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ori = np.array([a0x] * 4, dtype=np.float32) |
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zero_anchors = self.anchors + ori |
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x1 = zero_anchors[:, 0] |
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y1 = zero_anchors[:, 1] |
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x2 = zero_anchors[:, 2] |
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y2 = zero_anchors[:, 3] |
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x1, y1, x2, y2 = map(lambda x: x.reshape(self.anchor_num, 1, 1), [x1, y1, x2, y2]) |
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cx, cy, w, h = corner2center([x1, y1, x2, y2]) |
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disp_x = np.arange(0, size).reshape(1, 1, -1) * self.stride |
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disp_y = np.arange(0, size).reshape(1, -1, 1) * self.stride |
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cx = cx + disp_x |
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cy = cy + disp_y |
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zero = np.zeros((self.anchor_num, size, size), dtype=np.float32) |
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cx, cy, w, h = map(lambda x: x + zero, [cx, cy, w, h]) |
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x1, y1, x2, y2 = center2corner([cx, cy, w, h]) |
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self.all_anchors = np.stack([x1, y1, x2, y2]), np.stack([cx, cy, w, h]) |
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return True |
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