training_epoch_accuracy_visulizer.py

import pandas as pd
import matplotlib.pyplot as plt

def plot_training_results(csv_path):
    """
    Plots the training accuracy over epochs from the training results CSV file.

    Parameters:
    csv_path (str): Path to the training results CSV file.
    """
    # Load the training results from the CSV file
    results = pd.read_csv(csv_path)
    results.columns = results.columns.str.strip()  # Remove any leading/trailing whitespace from column names

    # Extract epochs and accuracy metrics
    epochs = results.index + 1  # Epochs are zero-indexed, so add 1
    mAP_0_5 = results['metrics/mAP50(B)']  # Mean Average Precision at IoU=0.5
    mAP_0_5_0_95 = results['metrics/mAP50-95(B)']  # Mean Average Precision at IoU=0.5:0.95

    # Plot the accuracy over epochs
    plt.figure(figsize=(10, 5))
    plt.plot(epochs, mAP_0_5, label='mAP@0.5')
    plt.plot(epochs, mAP_0_5_0_95, label='mAP@0.5:0.95')
    plt.xlabel('Epoch')
    plt.ylabel('Accuracy')
    plt.title('Accuracy Over Epochs')
    plt.legend()
    plt.grid(True)
    plt.show()

if __name__ == "__main__":
    plot_training_results('runs/detect/train/results.csv')