Computer Vision News - June 2022

54 Medical Imaging AI tool Confusion Matrix plt.figure() plot_confusion_matrix(cm, classes=class_names, title='Confusion matrix for Covid-19 Detection') Confusion matrix, without normalization [[23 2] [ 0 25]] history = hist print(history.history.keys()) dict_keys(['val_loss', 'val_accuracy', 'loss', 'accuracy']) Let’s plot the accuracy and loss values for both training and test sets: Predictions from X-Ray Images The following are the predictions for the x-ray images! imggg = cv2.imread('/content/drive/My Drive/Dataset/Predictior_Image/IM-0569-0001.jpeg') print("Actual: Negative covid-19 ") imggg = np.array(imggg)