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)
def decode_predictions(*args, **kwargs): return inception_v3.decode_predictions(*args, **kwargs)