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sted_visualize.py
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from cv2 import cv2
import numpy as np
import pandas as pd
import os
pred = pd.read_csv('./sted_feature/outputs/sted/test_yolo_fold_1.csv')
gt = pd.read_csv('./sted_feature/outputs/ground_truth/test_yolo_fold_1.csv')
path_save_frame = './sted_result/frame/'
path_save_video = './sted_result/video/'
# for index in range(len(pred['filename'])):
for index in range(1000):
city = str(pred['filename'][index])
video = str(pred['vid'][index])
frame_num = str(pred['frame_num'][index])
pred_x1 = pred['x1_60'][index]
pred_y1 = pred['y1_60'][index]
pred_x2 = pred['x2_60'][index]
pred_y2 = pred['y2_60'][index]
pred_center_x60, pred_center_y60 = int((pred_x1 + pred_x2) / 2), int(
(pred_y1 + pred_y2) / 2)
gt_x1 = gt['x1_60'][index]
gt_y1 = gt['y1_60'][index]
gt_x2 = gt['x2_60'][index]
gt_y2 = gt['y2_60'][index]
gt_center_x60, gt_center_y60 = int((gt_x1 + gt_x2) / 2), int(
(gt_y1 + gt_y2) / 2)
x1 = pred['x1_1'][index]
y1 = pred['y1_1'][index]
x2 = pred['x2_1'][index]
y2 = pred['y2_1'][index]
pred_center_x1, pred_center_y1 = int((x1 + x2) / 2), int((y1 + y2) / 2)
x1 = gt['x1_1'][index]
y1 = gt['y1_1'][index]
x2 = gt['x2_1'][index]
y2 = gt['y2_1'][index]
gt_center_x1, gt_center_y1 = int((x1 + x2) / 2), int((y1 + y2) / 2)
img = cv2.imread('/home/wangsen/ws/video2frame/' + city + '/' + video +
'/' + frame_num + '.png')
cv2.circle(img, (pred_center_x1, pred_center_y1), 5, (0, 255, 0), -1)
# cv2.circle(img, (gt_center_x1, gt_center_y1), 5, (255, 0, 0), -1)
cv2.line(img, (pred_center_x1, pred_center_y1),
(pred_center_x60, pred_center_y60), (0, 255, 0), 1)
cv2.line(img, (gt_center_x1, gt_center_y1), (gt_center_x60, gt_center_y60),
(255, 0, 0), 1)
# 预测
cv2.line(img, (pred_x1, pred_y1), (pred_x2, pred_y1), (0, 255, 0), 3)
cv2.line(img, (pred_x1, pred_y1), (pred_x1, pred_y2), (0, 255, 0), 3)
cv2.line(img, (pred_x2, pred_y1), (pred_x2, pred_y2), (0, 255, 0), 3)
cv2.line(img, (pred_x1, pred_y2), (pred_x2, pred_y2), (0, 255, 0), 3)
# gt
cv2.line(img, (gt_x1, gt_y1), (gt_x2, gt_y1), (255, 0, 0), 3)
cv2.line(img, (gt_x1, gt_y1), (gt_x1, gt_y2), (255, 0, 0), 3)
cv2.line(img, (gt_x2, gt_y1), (gt_x2, gt_y2), (255, 0, 0), 3)
cv2.line(img, (gt_x1, gt_y2), (gt_x2, gt_y2), (255, 0, 0), 3)
# cv2.putText(img, str(index), (pred_x1, pred_y1 + 10),
# cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)
# cv2.putText(img, str(index), (gt_x1, gt_y1 + 10), cv2.FONT_HERSHEY_SIMPLEX,
# 0.75, (0, 0, 255), 2)
cv2.imshow('', img)
cv2.waitKey(1)
print('Processing draw: ', city, '/', video, ' --- [ ', index, ' / ',
len(pred['filename']), ' ]')
# frame_city
city_dir_1 = ''.join([path_save_frame, city])
if not os.path.exists(city_dir_1):
os.mkdir(city_dir_1)
# frame_video
video_dir_1 = ''.join([city_dir_1, '/', video])
if not os.path.exists(video_dir_1):
os.mkdir(video_dir_1)
cv2.imwrite(
'/home/wangsen/ws/video2frame/' + city + '/' + video + '/' +
frame_num + '.png', img)
if cv2.waitKey(1) & 0xFF == ord('q'):
exit()
def read_video(path, res):
file_list = os.listdir(path)
for filename in file_list:
tmp_path = os.path.join(path, filename)
if tmp_path[-4:] == '.mp4':
res.append(tmp_path)
elif os.path.isdir(tmp_path):
# print("目录：", filename)
read_video(tmp_path, res)
'''
根据上面图片结果
保存视频
'''
root_path = '/home/wangsen/ws/video2frame/'
result_path = []
read_video(root_path, result_path)
for i in result_path:
city = i.split('/')[-2]
video = i.split('/')[-1]
fourcc = cv2.VideoWriter_fourcc(*'XVID')
# video_city
city_dir_2 = ''.join([path_save_video, city])
if not os.path.exists(city_dir_2):
os.mkdir(city_dir_2)
# # video_video
# video_dir_2 = ''.join([city_dir_2, '/', video])
# if not os.path.exists(video_dir_2):
# os.mkdir(video_dir_2)
out = cv2.VideoWriter(city_dir_2 + '/' + city + '_' + video[0:-4] + '.avi',
fourcc, 30, (1280, 720))
for idx in range(600):
img = cv2.imread('/home/wangsen/ws/video2frame/' + city + '/' + video +
'/' + str(idx) + '.png')
out.write(img)
cv2.imshow('', img)
cv2.waitKey(1)
print('Processing: ', city, '/', video, ' --- ', idx)
out.release()
# pd.DataFrame(val_feature_video_path).to_csv('./data/val_feature_video_path.csv')