gunjannandy/fetal_health_prediction.py

## fetal_health_prediction.py
# pick random test data sample from one batch
x = random.randint(0, len(Xtest) - 1)
# getting output; input shape (256, 256, 3) --> (1, 256, 256, 3)
output = model.predict(Xtest[x].reshape(1, -1))
pred = np.argmax(output[0])    # finding max
# Picking the label from class_names based on the model output
print("Prdicted: ", class_names[pred])
output_true = np.array(ytest)[x]
print("True: ", class_names[np.argmax(output_true)])
print("Probability: ", output[0][pred])
	# pick random test data sample from one batch
	x = random.randint(0, len(Xtest) - 1)
	# getting output; input shape (256, 256, 3) --> (1, 256, 256, 3)
	output = model.predict(Xtest[x].reshape(1, -1))
	pred = np.argmax(output[0]) # finding max
	# Picking the label from class_names based on the model output
	print("Prdicted: ", class_names[pred])
	output_true = np.array(ytest)[x]
	print("True: ", class_names[np.argmax(output_true)])
	print("Probability: ", output[0][pred])