cv (yolov5)
program that can find patterns or make decisions from a previously unseen dataset.
Note: Drone Computer Vision Repo w/ Datasets
1 - Video/Roboflow: Gather images for dataset
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We can film a video of the item we want to detect and then upload to Roboflow. On the Roboflow website, we can extract frames every X seconds to create a .jpg file each interval. Then we can begin labeling each image on Roboflow. |
Roboflow is a website where you upload images, label them, and export a zip file (images & .xml files).
Useful to share dataset and have 3 people label at the same time
1.1 - Unlabeled Images to Labeled Images
Unlabled | Labeled (Desired Outcome) |
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2 - Colab: Train Custom Model
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-The following website uses Python -here we set up libraries - collections of pre-written code that you can use to perform specific tasks -Prepare the dataset -Train the model -Evaluate the model performance with validation data -Export the model as .tflite file |
Open up Google Colab for Yolov5 Training
Follow this video for more details
3 - Export Model
Download the best.pt file to upload to Raspberry Pi.
Have a naming convention like '3-27-2024--300epochs-' Demo here
4 - Set up Pi - Installation
Python Library Versions located here
Ctrl + Alt + T |
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NOTE: (2:54) -click top left -preferences -raspberry pi configuration -tabs: interfaces -enable camera -reboot |
5 - Run on Pi
Ctrl + Alt + T |
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(Note: if on virtual machine for testing): Devices > Webcams > Check Integrated cam box |
Download your best.pt file after training, you can use Github or Google Drive |
cd yolov5 |
cp ~/Downloads/best.pt . |
gedit detect.py
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sudo python3 detect.py |
sudo python3 detect.py --weights 3-27-13-best.pt --source 0 or sudo python3 detect.py --weights best.pt --source 0 |
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