Furnish_AI / load_model.py
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import requests
import tensorflow as tf
# URL of the model file
url = "https://storage.googleapis.com/mediapipe-models/interactive_segmenter/magic_touch/float32/1/magic_touch.tflite"
# Send a HTTP request to the URL of the file, get is a method that sends a HTTP request to the server and fetches the response
response = requests.get(url)
# Write the response content to a file
with open('model.tflite', 'wb') as f:
f.write(response.content)
# Load the TFLite model
interpreter = tf.lite.Interpreter(model_path="model.tflite")
interpreter.allocate_tensors()