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| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| __author__ = '古溪' | |
| import numpy as np | |
| from typing import List | |
| def functools_reduce(a): | |
| # 使用functools內建模块 | |
| import functools | |
| import operator | |
| return functools.reduce(operator.concat, a) | |
| def minConnectPath(list_all: List[list]): | |
| list_nodo = list_all.copy() | |
| res = [] | |
| ept = [0, 0] | |
| def norm2(a, b): | |
| """计算两点之间的距离""" | |
| return ((a[0] - b[0]) ** 2 + (a[1] - b[1]) ** 2) ** 0.5 | |
| dict00 = {} # 格式 {距离,(起点坐标,终点坐标)} | |
| dict11 = {} # 格式 {距离,(起点坐标,终点坐标)} | |
| # 放入一个初始值 | |
| ept[0] = list_nodo[0] # left end point | |
| ept[1] = list_nodo[0] # right end point | |
| list_nodo.remove(list_nodo[0]) | |
| while list_nodo: | |
| for i in list_nodo: # i 待处理的 | |
| length0 = norm2(i, ept[0]) # 端点0终点距离 | |
| dict00[length0] = [i, ept[0]] | |
| length1 = norm2(ept[1], i) # 端点0终点距离 | |
| dict11[length1] = [ept[1], i] | |
| key0 = min(dict00.keys()) | |
| key1 = min(dict11.keys()) | |
| if key0 <= key1: | |
| ss = dict00[key0][0] | |
| ee = dict00[key0][1] | |
| res.insert(0, [list_all.index(ss), list_all.index(ee)]) | |
| list_nodo.remove(ss) | |
| ept[0] = ss | |
| else: | |
| ss = dict11[key1][0] | |
| ee = dict11[key1][1] | |
| res.append([list_all.index(ss), list_all.index(ee)]) | |
| list_nodo.remove(ee) | |
| ept[1] = ee | |
| dict00 = {} | |
| dict11 = {} | |
| path = functools_reduce(res) | |
| path = sorted(set(path), key=path.index) # 去重 | |
| return res, path | |
| def bbox_transfor_inv(radius_map, sin_map, cos_map, score_map, wclip=(2, 8), expend=1.0): | |
| xy_text = np.argwhere(score_map > 0) | |
| # sort the text boxes via the y axis | |
| xy_text = xy_text[np.argsort(xy_text[:, 0])] | |
| origin = xy_text | |
| radius = radius_map[xy_text[:, 0], xy_text[:, 1], :] | |
| sin = sin_map[xy_text[:, 0], xy_text[:, 1]] | |
| cos = cos_map[xy_text[:, 0], xy_text[:, 1]] | |
| dtx = radius[:, 0] * cos * expend | |
| dty = radius[:, 0] * sin * expend | |
| ddx = radius[:, 1] * cos * expend | |
| ddy = radius[:, 1] * sin * expend | |
| topp = origin + np.stack([dty, dtx], axis=-1) | |
| botp = origin - np.stack([ddy, ddx], axis=-1) | |
| width = (radius[:, 0] + radius[:, 1]) // 3 | |
| width = np.clip(width, wclip[0], wclip[1]) | |
| top1 = topp - np.stack([width * cos, -width * sin], axis=-1) | |
| top2 = topp + np.stack([width * cos, -width * sin], axis=-1) | |
| bot1 = botp - np.stack([width * cos, -width * sin], axis=-1) | |
| bot2 = botp + np.stack([width * cos, -width * sin], axis=-1) | |
| bbox = np.stack([top1, top2, bot2, bot1], axis=1)[:, :, ::-1] | |
| bboxs = np.zeros((bbox.shape[0], 9), dtype=np.float32) | |
| bboxs[:, :8] = bbox.reshape((-1, 8)) | |
| bboxs[:, 8] = score_map[xy_text[:, 0], xy_text[:, 1]] | |
| return bboxs | |