108 lines
4.0 KiB
Python
108 lines
4.0 KiB
Python
import cv2
|
||
import numpy as np
|
||
import torch
|
||
# from loguru import logger
|
||
|
||
def pannel_post_process(preds, pars):
|
||
# pars={'solar':0}
|
||
'''
|
||
将光伏板上覆盖物、裂缝识别出来
|
||
'''
|
||
# print(preds[0])
|
||
# logger.info('\n分类结果返回：%s'%preds)
|
||
preds = torch.tensor(preds[0])
|
||
preds = preds.tolist()
|
||
preds = [[*sublist[:-1], int(sublist[-1])] for sublist in preds] # 类别从浮点型转为整型
|
||
# print(preds)
|
||
# 设置空的列表
|
||
# 1、判断类别中哪些有太阳能板？取出太阳能板检测结果，并取出覆盖物、裂缝检测结果。
|
||
preds_solar = []
|
||
preds_others = []
|
||
for i in range(len(preds)):
|
||
if preds[i][5] in pars['objs']: # 识别为光伏板
|
||
preds_solar.append(preds[i])
|
||
else: # 识别为裂缝、覆盖物
|
||
preds_others.append(preds[i])
|
||
|
||
return point_in_rectangle(preds_others, preds_solar)
|
||
|
||
|
||
def center_coordinate(boundbxs):
|
||
'''
|
||
根据检测矩形框，得到其矩形长度和宽度
|
||
输入：两个对角坐标xyxy
|
||
输出：矩形框重点坐标xy
|
||
'''
|
||
boundbxs_x1 = boundbxs[0]
|
||
boundbxs_y1 = boundbxs[1]
|
||
boundbxs_x2 = boundbxs[2]
|
||
boundbxs_y2 = boundbxs[3]
|
||
center_x = 0.5 * (boundbxs_x1 + boundbxs_x2)
|
||
center_y = 0.5 * (boundbxs_y1 + boundbxs_y2)
|
||
return center_x, center_y
|
||
|
||
|
||
def fourcorner_coordinate(boundbxs):
|
||
'''
|
||
通过矩形框对角xyxy坐标，得到矩形框轮廓
|
||
输入：两个对角坐标xyxy
|
||
输出：矩形框四个角点坐标，以contours顺序。
|
||
'''
|
||
boundbxs_x1 = boundbxs[0]
|
||
boundbxs_y1 = boundbxs[1]
|
||
boundbxs_x2 = boundbxs[2]
|
||
boundbxs_y2 = boundbxs[3]
|
||
wid = boundbxs_x2 - boundbxs_x1
|
||
hei = boundbxs_y2 - boundbxs_y1
|
||
boundbxs_x3 = boundbxs_x1 + wid
|
||
boundbxs_y3 = boundbxs_y1
|
||
boundbxs_x4 = boundbxs_x1
|
||
boundbxs_y4 = boundbxs_y1 + hei
|
||
contours_rec = [[boundbxs_x1, boundbxs_y1], [boundbxs_x3, boundbxs_y3], [boundbxs_x2, boundbxs_y2],
|
||
[boundbxs_x4, boundbxs_y4]]
|
||
return contours_rec
|
||
|
||
|
||
def point_in_rectangle(preds_others, preds_solar):
|
||
'''
|
||
遍历所有光伏板异常目标，并输出
|
||
'''
|
||
if not preds_solar:
|
||
return [[],'']
|
||
|
||
preds = []
|
||
for i in range(len(preds_others)):
|
||
for solar in preds_solar:
|
||
solar_contour = fourcorner_coordinate(solar)
|
||
solar_contour = np.array(solar_contour, dtype=np.float32)
|
||
center_x, center_y = center_coordinate(preds_others[i])
|
||
# print(cv2.pointPolygonTest(solar_contour, (center_x, center_y), False))
|
||
if cv2.pointPolygonTest(solar_contour, (center_x, center_y), False) == 1:
|
||
preds.append(preds_others[i])
|
||
|
||
# logger.info('\n分类结果返回：%s' % preds)
|
||
return [preds,'']
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 对应DJI_20230306140129_0001_Z_165.jpg检测结果
|
||
# preds=[[6.49000e+02, 2.91000e+02, 1.07900e+03, 7.33000e+02, 9.08165e-01, 3.00000e+00],
|
||
# [8.11000e+02, 2.99000e+02, 1.31200e+03, 7.65000e+02, 8.61268e-01, 3.00000e+00],
|
||
# [7.05000e+02, 1.96000e+02, 7.19000e+02, 2.62000e+02, 5.66877e-01, 0.00000e+00]]
|
||
|
||
# 对应DJI_20230306152702_0001_Z_562.jpg检测结果
|
||
preds = [[7.62000e+02, 7.14000e+02, 1.82800e+03, 9.51000e+02, 9.00902e-01, 3.00000e+00],
|
||
[2.00000e+01, 3.45000e+02, 1.51300e+03, 6.71000e+02, 8.81440e-01, 3.00000e+00],
|
||
[8.35000e+02, 8.16000e+02, 8.53000e+02, 8.30000e+02, 7.07651e-01, 0.00000e+00],
|
||
[1.35600e+03, 4.56000e+02, 1.42800e+03, 4.94000e+02, 6.70549e-01, 2.00000e+00]]
|
||
print('before :\n ', preds)
|
||
# preds=torch.tensor(preds) #返回的预测结果
|
||
imgwidth = 1920
|
||
imgheight = 1680
|
||
pars = {'imgSize': (imgwidth, imgheight), 'wRation': 1 / 6.0, 'hRation': 1 / 6.0, 'smallId': 0, 'bigId': 3,
|
||
'newId': 4, 'recScale': 1.2}
|
||
# 'smallId':0(国旗)，'bigId':3(船只),wRation和hRation表示判断的阈值条件，newId--新目标的id
|
||
# yyy = channel2_post_process([preds], pars) # 送入后处理函数
|
||
#
|
||
# print('after :\n ', yyy)
|