import tensorflow as tf
interpreter = tf.lite.Interpreter(model_path="C:/Users/asmaa/Documents/GitHub/MLKitDemo/app/src/main/assets/detect.tflite")
interpreter.allocate_tensors()
# Print input shape and type
print(interpreter.get_input_details()[0]['shape']) # Example: [1 224 224 3]
print(interpreter.get_input_details()[0]['dtype']) # Example: <class 'numpy.float32'>
# Print output shape and type
print(interpreter.get_output_details()[0]['shape']) # Example: [1 1000]
print(interpreter.get_output_details()[0]['dtype']) # Example: <class 'numpy.float32'>