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5 Commits

Author SHA1 Message Date
myh
45db741f35 删除无用文件 2025-04-19 13:08:24 +08:00
myh
5df0e15baf 静态图片测试 2025-04-19 13:08:15 +08:00
myh
5e72ac28cc yolo模型文件 2025-04-19 13:07:47 +08:00
myh
5b61b48d50 依赖包 2025-04-19 13:07:37 +08:00
myh
160bb2e365 测试图片 2025-04-19 13:07:28 +08:00
7 changed files with 106 additions and 36 deletions

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@ -13,7 +13,7 @@ from ultralytics import YOLO
# 添加YOLOv8模型初始化
yolo_model = YOLO("yolov8n.pt") # 可替换为yolov8s/m/l等
yolo_model.to('cuda') # 启用GPU加速(可选)
yolo_model.to('cuda') # 启用GPU加速
def sift_registration(img1, img2):
@ -125,6 +125,7 @@ def Images_matching(img_base, img_target):
src_pts = np.array([kp1[m.queryIdx].pt for m in good]) # 查询图像的特征描述子索引 # 134, 2
dst_pts = np.array([kp2[m.trainIdx].pt for m in good]) # 训练(模板)图像的特征描述子索引
if len(src_pts) <= 4:
print("Not enough matches are found - {}/{}".format(len(good), 4))
return 0, None, 0
else:
# print(len(dst_pts), len(src_pts), "配准坐标点")
@ -204,38 +205,66 @@ if __name__ == '__main__':
time_all = 0
dots = 0
i = 0
fourcc = cv2.VideoWriter_fourcc(*'XVID')
capture = cv2.VideoCapture("video/20190926_141816_1_8/20190926_141816_1_8/infrared.mp4")
capture2 = cv2.VideoCapture("video/20190926_141816_1_8/20190926_141816_1_8/visible.mp4")
fps = capture.get(cv2.CAP_PROP_FPS)
out = cv2.VideoWriter('output2.mp4', fourcc, fps, (640, 480))
# 持续读取摄像头数据
while True:
read_code, frame = capture.read() # 红外帧
read_code2, frame2 = capture2.read() # 可见光帧
if not read_code:
break
i += 1
# frame = cv2.resize(frame, (1920, 1080))
# frame2 = cv2.resize(frame2, (640, 512))
# fourcc = cv2.VideoWriter_fourcc(*'XVID')
# capture = cv2.VideoCapture("video/20190926_141816_1_8/20190926_141816_1_8/infrared.mp4")
# capture2 = cv2.VideoCapture("video/20190926_141816_1_8/20190926_141816_1_8/visible.mp4")
# fps = capture.get(cv2.CAP_PROP_FPS)
# out = cv2.VideoWriter('output2.mp4', fourcc, fps, (640, 480))
# # 持续读取摄像头数据
# while True:
# read_code, frame = capture.read() # 红外帧
# read_code2, frame2 = capture2.read() # 可见光帧
# if not read_code:
# break
# i += 1
# # frame = cv2.resize(frame, (1920, 1080))
# # frame2 = cv2.resize(frame2, (640, 512))
#
# # 转换为灰度图(红外图像处理)
# frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#
# # 调用main函数进行融合和检测
# flag, fusion, dot = main(frame2, frame_gray)
#
# if flag == 1:
# # 显示带检测结果的融合图像
# cv2.imshow("Fusion with YOLOv8 Detection", fusion)
# out.write(fusion)
#
# if cv2.waitKey(1) == ord('q'):
# break
# # 释放资源
# capture.release()
# capture2.release()
# cv2.destroyAllWindows()
# ave = time_all / i
# print(ave, "平均时间")
# cv2.destroyAllWindows()
# === 新增静态图片测试代码 ===
# 输入可见光和红外图像路径
visible_path = "../test_images/visible.jpg" # 可见光图片路径
infrared_path = "../test_images/infrared.jpg" # 红外图片路径
# 读取图像
img_visible = cv2.imread(visible_path)
img_infrared = cv2.imread(infrared_path)
if img_visible is None or img_infrared is None:
print("Error: 图片加载失败,请检查路径!")
exit()
# 转换为灰度图(红外图像处理)
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
img_inf_gray = cv2.cvtColor(img_infrared, cv2.COLOR_BGR2GRAY)
# 调用main函数进行融合和检测
flag, fusion, dot = main(frame2, frame_gray)
# 执行融合与检测
flag, fusion_result, _ = main(img_visible, img_inf_gray)
if flag == 1:
# 显示带检测结果的融合图像
cv2.imshow("Fusion with YOLOv8 Detection", fusion)
out.write(fusion)
if cv2.waitKey(1) == ord('q'):
break
# 释放资源
capture.release()
capture2.release()
cv2.destroyAllWindows()
ave = time_all / i
print(ave, "平均时间")
# 显示并保存结果
cv2.imshow("Fusion with Detection", fusion_result)
cv2.imwrite("../output/fusion_result.jpg", fusion_result)
cv2.waitKey(0)
cv2.destroyAllWindows()
else:
print("融合失败!")

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requirements.txt Normal file
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@ -0,0 +1,41 @@
certifi==2025.1.31
charset-normalizer==3.4.1
colorama==0.4.6
contourpy==1.3.2
cycler==0.12.1
filelock==3.18.0
fonttools==4.57.0
fsspec==2025.3.2
idna==3.10
Jinja2==3.1.6
kiwisolver==1.4.8
MarkupSafe==3.0.2
matplotlib==3.10.1
mpmath==1.3.0
networkx==3.4.2
numpy==2.1.1
opencv-python==4.11.0.86
packaging==24.2
pandas==2.2.3
pillow==11.2.1
psutil==7.0.0
py-cpuinfo==9.0.0
pyparsing==3.2.3
python-dateutil==2.9.0.post0
pytz==2025.2
PyYAML==6.0.2
requests==2.32.3
scipy==1.15.2
seaborn==0.13.2
setuptools==78.1.0
six==1.17.0
sympy==1.13.1
torch==2.6.0+cu124
torchaudio==2.6.0+cu124
torchvision==0.21.0+cu124
tqdm==4.67.1
typing_extensions==4.13.2
tzdata==2025.2
ultralytics==8.3.111
ultralytics-thop==2.0.14
urllib3==2.4.0

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