This repo consists of code to allow chatgpt to effectively classify images of circuits. This algoirthm consists of several steps. First a scene is classified though an end-to-end fine-tuned deep neural network Xception. If it is a circuit, then YOLO uses CNNs to draw segmentations around various items. Then an algorithm uses said segmentations to essentially convert the image to a sentence describing the circuit which will be fed into chatgpt. The response from chatgpt is the final output.
- Data: The original image data
- Output: The ouput images from YOLO segmentation algorithm
- Circuit Classifier: Has Code involved with Training and Using Segmentation algorithm.
- PredictAndTrain.py: Predicts or Trains Yolo algorithm
- segmentationToOutput.py: converts segmentation output to chatgpt text input
- boundingBoxToOutput.py: No longer used but converted bounding boxes around objects to chatgpt input
- best.pt: Best performing yolo model weights
- Graph Generation: Generates Matplotlib Graphs For Paper
- chatGPTInterface: Utilizes chatGPT by feeding input text and printing output text
- FullProgram.py: Runs algorithm from YOLO to chatgpt Output