class Apparel:
def __init__(self):
self.app = ClarifaiApp(api_key='986fb613cdcf42d781e69646ce92d7b5')
self.model = Model(self.app.api,
model_id='72c523807f93e18b431676fb9a58e6ad')
self.fmodel = Model(self.app.api,
model_id='e466caa0619f444ab97497640cefc4dc')
def detect(self, frame, height, width):
response = self.model.predict_by_filename(frame)
items = []
boxes = []
if 'regions' in response['outputs'][0]['data']:
for region in response['outputs'][0]['data']['regions']:
bb = region['region_info']['bounding_box']
boxes.append([
int(height * bb['top_row']),
int(height * bb['bottom_row']),
int(width * bb['left_col']),
int(width * bb['right_col'])
])
items.append(region['data']['concepts'][0]['name'])
return items, boxes
def detect_famous(self, frame, height, width):
response = self.fmodel.predict_by_filename(frame)
celebs = []
boxes = []
if 'regions' in response['outputs'][0]['data']:
regions = response['outputs'][0]['data']['regions']
for region in regions:
if region['data']['concepts'][0]['value'] > 0.5:
celebs.append(region['data']['concepts'][0]['name'])
bb = region['region_info']['bounding_box']
boxes.append([
int(height * bb['top_row']),
int(height * bb['bottom_row']),
int(width * bb['left_col']),
int(width * bb['right_col'])
])
return celebs, boxes
def test_model_evaluate(mock_http_client): # type: (mock.Mock) -> None
mock_execute_request = mock_request(
mock_http_client, """
{
"status": {
"code": 10000,
"description": "Ok"
},
"model_version": {
"id": "@modelVersionID",
"created_at": "2017-01-01T00:00:00.000000Z",
"status": {
"code": 21100,
"description": "Model trained successfully"
},
"active_concept_count": 2,
"metrics": {
"status": {
"code": 21303,
"description": "Model is queued for evaluation."
}
},
"total_input_count": 30
}
}
""")
app = ClarifaiApp()
model = Model(app.api, model_id='@modelID')
model.model_version = '@modelVersionID'
response = model.evaluate()
assert response['status']['code'] == 10000
assert_request(mock_execute_request, 'POST',
'/v2/models/@modelID/versions/@modelVersionID/metrics',
'{}')
def test_predict_with_model_id(self):
""" test initialize model object """
# make model from model_id
m = Model(self.app.api, model_id='eee28c313d69466f836ab83287a54ed9')
m.predict_by_url(sample_inputs.METRO_IMAGE_URL)
def __init__(self):
self.app = ClarifaiApp(api_key='986fb613cdcf42d781e69646ce92d7b5')
self.model = Model(self.app.api,
model_id='72c523807f93e18b431676fb9a58e6ad')
self.fmodel = Model(self.app.api,
model_id='e466caa0619f444ab97497640cefc4dc')
def test_predict_with_model_id(self):
""" test initialize model object """
# make model from model_id
m = Model(self.app.api, model_id='eee28c313d69466f836ab83287a54ed9')
m.predict_by_url(urls[0])
def test_predict_with_model_id(self): """ test initialize model object """ # make model from model_id m = Model(self.app.api, model_id='eee28c313d69466f836ab83287a54ed9') m.predict_by_url(sample_inputs.METRO_IMAGE_URL)