Training a PyTorch YOLOv7 machine learning model

ai/README.md

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+# Training the PyTorch Localizer and Detector
+
+## Content
+
+The `model.py` files contains a Python class called `Dataset`, which has methods for manipulating datasets of SkyScan images and training models on them.  There are also some example functions that use the class, including `revised_sequence()`, which runs an entire data analysis pipeline.  The steps in that pipeline including ingesting the imagery, training a localizer (which finds bounding boxes), using the localizer to find bounding boxes on additional images, training a detector (which finds bounding boxes and aircraft class), and testing the performance of localizer and detector with testing data.
+
+The pipeline will need to be adapted to meet your specific needs.  Each time a model is trained or used, YOLOv7 outputs the results to a folder.  To retrain a model or rerun a test, the corresponding folder name should be changed in the code to avoid a collision.  On the other hand, if you've already trained a model or run a test and are rerunning the code, you can instead comment out the corresponding `.train()` and `.test()` calls to save time.  In general, lines ending with `##` in `revised_sequence()` are time-intensive steps that only need to be run once, and can be commented out to save time if rerunning the code.
+
+## Setup
+
+Install the [YOLOv7 repo](https://github.com/WongKinYiu/yolov7), following the instructions there.  Then, copy the following files into the root folder of your YOLOv7 installation:
+* `model.py`
+* `test2.py`
+* `localizer_rev2.yaml`
+* `detector_rev2.yaml`
+* `taxon.json`
+
+Copy the following files into the `utils` folder:
+* `metrics2.py`
+* `datasets2.py`
+
+Then, edit the `model.py` file's `revised_sequence()` method and update the file paths to point to the appropriate folders for your system.  File paths in `localizer_rev2.yaml` and `detector_rev2.yaml` will also need to be updated.
+
+Finally, from the YOLOv7 root folder, run:
+`./model.py`
+
+## License
+
+The contents of this folder are derived from https://github.com/WongKinYiu/yolov7 and are being released under the GNU General Public License v3.0. (The remainder of this repo is released under the Apache License 2.0.)