YOLOv7 cars detection

The following example shows how to use the YOLOv7 model for cars (and other vehicles) detection in aerial or satellite images.


The example is based on the ITCVD cars detection dataset. It provides aerial images with 10 cm/px resolution. Annotation bounding boxes for the cars are provided.

Training tutorial

The entire training process has been gathered in `a tutorial notebook in jupyter notebook <https://github.com/PUTvision/qgis-plugin-deepness/blob/master/tutorials/detection/cars_yolov7/car_detection__prepare_and_train.ipynb>’_:


Example inference

Run QGIS, next add “Poznan 2022 aerial” map using QuickMapServices plugin.

Alternatively you can use any other aerial or satellite map with resolution of at least 10 cm/pixel


Then run our plugin and set parameters like in the screenshot below. You can find the pre-trained onnx model at https://chmura.put.poznan.pl/s/vgOeUN4H4tGsrGm. Push the Run button to start processing.


Another inference on random street in Poznan:


And output mask for an Grunwald district in Poznan: