def home_appliance(): img = image.img_to_array( image.load_img(BytesIO(base64.b64decode(request.form['b64'])), target_size=(224, 224))) / 255. payload = {"instances": [{'input_image': img.tolist()}]} r = requests.post( 'http://163.122.226.25:9001/v1/models/ApplianceDamageAnalyzer:predict', json=payload) classes = [ 'building', 'minor', 'moderate', 'nodamage', 'severe', 'vehicle' ] pred = json.loads(r.content.decode('utf-8')) return jsonify( inception_v3.decode_predictions(np.array(pred['predictions'])))
def decode_predictions(*args, **kwargs): return inception_v3.decode_predictions(*args, **kwargs)