Code coverage integration

.codecov.yml

@@ -5,7 +5,7 @@ codecov:
 coverage:
   precision: 2
   round: down
-  range: "70...100"
+  range: "30...100"
 
   status:
     project: yes

.travis.yml

@@ -25,7 +25,7 @@ script:
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/yolo-tiny.h5
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/essential-v4/pretrained-yolov3.h5
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/essential-v4/hololens-ex-60--loss-2.76.h5
-  - pytest -v
+  - pytest -m recognition -v
 after_success:
   - codecov
   - coverage

test/test_custom_recognition.py

@@ -17,7 +17,7 @@ def images_to_image_array():
 
 
 
-
+@pytest.mark.recognition
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 def test_custom_recognition_model_resnet():
@@ -35,7 +35,7 @@ def test_custom_recognition_model_resnet():
     assert isinstance(predictions[0], str)
     assert isinstance(probabilities[0], str)
 
-
+@pytest.mark.recognition
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 def test_custom_recognition_full_model_resnet():
@@ -51,7 +51,7 @@ def test_custom_recognition_full_model_resnet():
     assert isinstance(predictions[0], str)
     assert isinstance(probabilities[0], str)
 
-
+@pytest.mark.recognition
 @pytest.mark.densenet
 @pytest.mark.recognition_custom
 def test_custom_recognition_model_densenet():
@@ -70,7 +70,7 @@ def test_custom_recognition_model_densenet():
 
 
 
-
+@pytest.mark.recognition
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi
@@ -93,7 +93,7 @@ def test_custom_recognition_model_resnet_multi():
         assert isinstance(result["predictions"][0], str)
         assert isinstance(result["percentage_probabilities"][0], str)
 
-
+@pytest.mark.recognition
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi
@@ -115,7 +115,7 @@ def test_custom_recognition_full_model_resnet_multi():
         assert isinstance(result["predictions"][0], str)
         assert isinstance(result["percentage_probabilities"][0], str)
 
-
+@pytest.mark.recognition
 @pytest.mark.densenet
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi

test/test_model_training.py

@@ -21,6 +21,7 @@ def clear_keras_session():
 @pytest.mark.training
 @pytest.mark.training_resnet
 @pytest.mark.resnet
+@pytest.mark.recognition
 def test_resnet_training(clear_keras_session):
 
     trainer = ModelTraining()
@@ -39,6 +40,7 @@ def test_resnet_training(clear_keras_session):
 @pytest.mark.training
 @pytest.mark.training_squeezenet
 @pytest.mark.squeezenet
+@pytest.mark.recognition
 def test_squeezenet_training(clear_keras_session):
 
     trainer = ModelTraining()
@@ -57,6 +59,7 @@ def test_squeezenet_training(clear_keras_session):
 @pytest.mark.training
 @pytest.mark.training_inception_v3
 @pytest.mark.inception_v3
+@pytest.mark.recognition
 def test_inception_v3_training(clear_keras_session):
 
     trainer = ModelTraining()
@@ -75,6 +78,7 @@ def test_inception_v3_training(clear_keras_session):
 @pytest.mark.training
 @pytest.mark.training_densenet
 @pytest.mark.densenet
+@pytest.mark.recognition
 def test_densenet_training(clear_keras_session):
 
     trainer = ModelTraining()