The EDA, model development, and evaluation of a binary image classifier to detect emergency vehicles.
There are several notebooks that contain starter code for the model and also explains the dataset version that was used to train a binary emergency vehicle classifier. The dataset and weights reside on the EC2 instance called Training_Big_Boy. To ssh into this instance, you will need the justin_training_gpu.pem file, which can be found in an S3 bucket called lokoai-it-security.
There are several notebooks in this repo, but the two most important are listed below:
emergency_vehicle_eda.ipynbcontains EDA related to the emergency_vehicle datasetemergency_vehicle_model_dev.ipynbhas starter code to building the model and loading datayolo_plus_emergency_dev.ipynba PoC to see the results of linking a pre-trained yolo model to the emergency vehicle classifier. Results weren't satisfactory.
A simple way to improve the models performance is to switch to a much more powerful SSD model, such as CLIP. Example code for using CLIP as a single shot detector is located in the CLIP_dev.ipynb