# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from flash.core.data.utils import download_data
from flash.image import ObjectDetector
# 1. Download the data
# Dataset Credit: https://www.kaggle.com/ultralytics/coco128
download_data(
"https://github.com/zhiqwang/yolov5-rt-stack/releases/download/v0.3.0/coco128.zip",
"data/")
# 2. Load the model from a checkpoint
model = ObjectDetector.load_from_checkpoint(
"https://flash-weights.s3.amazonaws.com/object_detection_model.pt")
# 3. Detect the object on the images
predictions = model.predict([
"data/coco128/images/train2017/000000000025.jpg",
"data/coco128/images/train2017/000000000520.jpg",
"data/coco128/images/train2017/000000000532.jpg",
])
print(predictions)
def test_load_from_checkpoint_dependency_error():
with pytest.raises(ModuleNotFoundError,
match=re.escape("'lightning-flash[image]'")):
ObjectDetector.load_from_checkpoint("not_a_real_checkpoint.pt")