"This project allows you to use YOLOv8 with a DJI Tello Drone for real-time object detection streaming on your computer! You can control the drone with the Tello app and also save the detection results as a video." Notes The TelloCV_GitHubScript.py script features comments/annotations to ...
训练步骤如下: 将数据集放入Origin_dataset文件夹中,运行data_prepossess.ipynb的所有步骤,这部分将把数据集转换为适合输入YOLOv7架构的形式。 之后在终端中输入 python train.py 即可开始训练,训练结果在runs/train文件夹中。 最新的训练版本在runs/train/exp7中,之后的测试也将使用这里的参数。
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$ git clone https://github.com/ssling0817/UAV_Object_Detection $ cd PyTorch-YOLOv3/ $ sudo pip3 install -r requirements.txt Visit https://github.com/ssling0817/UAV_Object_Detection for detail operation. Data augmentation Brightness conversion def brightness(img, value): hsv = cv2.cvtColor...
Refer to zed_tensorrt_yolov8_onnx for guidance.Refer to setup_ptp.txt for camera stream synchronization instructions.Run the following commands in each build folder:./yolo_onnx_zed -s ../../model/exported_small/real_and_synthetic.onnx mixed_yolos.engine ./multi_cam_obj_tracking ../../...
How to do? $ git clone https://github.com/AICT-CVAI/Object-Detection-Drone && cd Object-Detection-Drone example. yolov5 $ cd yolov5 $ pip install -r requirements.txt $ python3 ui2.py Output Detection Results UI structure About...
Implement of vehicle flow statistics based on tensorflow and yolo3. New version with GUI: https://github.com/LeiWang1999/VehicleFlowDetection - Starrynightzyq/Drone_Vehicle_Flow_Detection
python docker computer-vision deep-learning drone yolo object-detection darknet darkflow tello tinyyolo tellodrone Updated Oct 6, 2020 Python fvilmos / tello_object_tracking Star 27 Code Issues Pull requests DJI Tello Drone tracks a moving object (a face or a person) on the horizontal/ve...
Here are 14 public repositories matching this topic... Language:All Sort:Most stars durner/yolo-autonomous-drone Star76 YOLO Autonomous Drone - Deep Learning Person Detection: The YOLO Drone localizes and follows people with the help of the YOLO Deep Network ...
1.5GB, downloadable from GitHub (as in, literally from GitHub) (download link) Metadata in YOLO format Categories: sheep, cattle, seal, camel, kiang, zebra (some images also include un-annotated birds) Vehicle type: drone Image information: 14,366 images, typically 640x640 Annotation informati...