Code coverage integration

.codecov.yml

@@ -0,0 +1,26 @@
+codecov:
+  notify:
+    require_ci_to_pass: yes
+
+coverage:
+  precision: 2
+  round: down
+  range: "70...100"
+
+  status:
+    project: yes
+    patch: yes
+    changes: no
+
+parsers:
+  gcov:
+    branch_detection:
+      conditional: yes
+      loop: yes
+      method: no
+      macro: no
+
+comment:
+  layout: "header, diff"
+  behavior: default
+  require_changes: no

.travis.yml

@@ -13,7 +13,6 @@ script:
   - cd test
   - mkdir data-models
   - mkdir data-temp
-  - mkdir data-datasets
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/DenseNet-BC-121-32.h5
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/inception_v3_weights_tf_dim_ordering_tf_kernels.h5
   - wget -P data-models/ https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/resnet50_weights_tf_dim_ordering_tf_kernels.h5
@@ -27,6 +26,9 @@ script:
   - 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
+after_success:
+  - codecov
+  - coverage
 
 
 

README.md

@@ -1,6 +1,6 @@
 # ImageAI (v2.1.3)
 
-[![Build Status](https://travis-ci.com/OlafenwaMoses/ImageAI.svg?branch=master)](https://travis-ci.com/OlafenwaMoses/ImageAI)  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/OlafenwaMoses/ImageAI/blob/master/LICENSE)
+[![Build Status](https://travis-ci.com/OlafenwaMoses/ImageAI.svg?branch=master)](https://travis-ci.com/OlafenwaMoses/ImageAI)  [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/OlafenwaMoses/ImageAI/blob/master/LICENSE)  [![codecov](https://codecov.io/gh/TechnionYP5777/project-name/branch/master/graph/badge.svg)](https://codecov.io/gh/OlafenwaMoses/ImageAI)  [![Build Status](https://travis-ci.org/TechnionYP5777/project-name.png)](https://codecov.io/gh/OlafenwaMoses/ImageAI)
 
 A python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple
  and few lines of code.

test/data-datasets/hololens/json/detection_config.json

@@ -0,0 +1,31 @@
+{
+    "anchors" : [
+        [
+            59,
+            48,
+            131,
+            79,
+            211,
+            210
+        ],
+        [
+            0,
+            0,
+            0,
+            0,
+            0,
+            0
+        ],
+        [
+            0,
+            0,
+            0,
+            0,
+            0,
+            0
+        ]
+    ],
+    "labels" : [
+        "hololens"
+    ]
+}

test/test_custom_object_detection.py

@@ -14,15 +14,20 @@
 model_json = os.path.join(main_folder, "data-json", "detection_config.json")
 
 
-
-@pytest.mark.detection
-@pytest.mark.yolov3
-@pytest.mark.custom_detection
-def test_object_detection_yolov3():
+@pytest.fixture
+def clear_keras_session():
     try:
         keras.backend.clear_session()
     except:
         None
+
+
+
+@pytest.mark.detection
+@pytest.mark.yolov3
+@pytest.mark.custom_detection
+def test_object_detection_yolov3(clear_keras_session):
+
     detector = CustomObjectDetection()
     detector.setModelTypeAsYOLOv3()
     detector.setModelPath(model_path)
@@ -61,11 +66,7 @@ def test_object_detection_yolov3():
 @pytest.mark.yolov3
 @pytest.mark.custom_detection
 @pytest.mark.array_io
-def test_object_detection_yolov3_array_io():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+def test_object_detection_yolov3_array_io(clear_keras_session):
 
     image_input_array = cv2.imread(image_input)
 

test/test_custom_recognition.py

@@ -17,14 +17,11 @@ def images_to_image_array():
 
 
 
+
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 def test_custom_recognition_model_resnet():
 
-    try:
-        keras.backend.clear_session()
-    except:
-        None
 
     predictor = CustomImagePrediction()
     predictor.setModelTypeAsResNet()
@@ -42,10 +39,7 @@ def test_custom_recognition_model_resnet():
 @pytest.mark.resnet
 @pytest.mark.recognition_custom
 def test_custom_recognition_full_model_resnet():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = CustomImagePrediction()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_full_resnet_ex-001_acc-0.119792.h5"))
     predictor.setJsonPath(model_json=os.path.join(main_folder, "data-json", "idenprof.json"))
@@ -61,10 +55,7 @@ def test_custom_recognition_full_model_resnet():
 @pytest.mark.densenet
 @pytest.mark.recognition_custom
 def test_custom_recognition_model_densenet():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = CustomImagePrediction()
     predictor.setModelTypeAsDenseNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_densenet-0.763500.h5"))
@@ -84,10 +75,7 @@ def test_custom_recognition_model_densenet():
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi
 def test_custom_recognition_model_resnet_multi():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = CustomImagePrediction()
     predictor.setModelTypeAsResNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_resnet.h5"))
@@ -110,10 +98,7 @@ def test_custom_recognition_model_resnet_multi():
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi
 def test_custom_recognition_full_model_resnet_multi():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = CustomImagePrediction()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_full_resnet_ex-001_acc-0.119792.h5"))
     predictor.setJsonPath(model_json=os.path.join(main_folder, "data-json", "idenprof.json"))
@@ -135,10 +120,7 @@ def test_custom_recognition_full_model_resnet_multi():
 @pytest.mark.recognition_custom
 @pytest.mark.recognition_multi
 def test_custom_recognition_model_densenet_multi():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = CustomImagePrediction()
     predictor.setModelTypeAsDenseNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_densenet-0.763500.h5"))

test/test_custom_video_detection.py

@@ -14,18 +14,21 @@
 model_json = os.path.join(main_folder, "data-json", "detection_config.json")
 
 
+@pytest.fixture
+def clear_keras_session():
+    try:
+        keras.backend.clear_session()
+    except:
+        None
+
 
 @pytest.mark.detection
 @pytest.mark.custom_detection
 @pytest.mark.video_detection
 @pytest.mark.custom_video_detection
 @pytest.mark.yolov3
-def test_custom_video_detection_yolov3():
+def test_custom_video_detection_yolov3(clear_keras_session):
 
-    try:
-        keras.backend.clear_session()
-    except:
-        None
 
     detector = CustomVideoObjectDetection()
     detector.setModelTypeAsYOLOv3()
@@ -46,12 +49,8 @@ def test_custom_video_detection_yolov3():
 @pytest.mark.custom_video_detection
 @pytest.mark.yolov3
 @pytest.mark.custom_video_detection_analysis
-def test_custom_video_detection_yolov3_analysis():
+def test_custom_video_detection_yolov3_analysis(clear_keras_session):
 
-    try:
-        keras.backend.clear_session()
-    except:
-        None
 
     detector = CustomVideoObjectDetection()
     detector.setModelTypeAsYOLOv3()

test/test_detection_model_training.py

@@ -12,17 +12,21 @@
 pretrained_model = os.path.join(main_folder, "data-models", "pretrained-yolov3.h5")
 
 
+@pytest.fixture
+def clear_keras_session():
+    try:
+        keras.backend.clear_session()
+    except:
+        None
+
+
 @pytest.mark.detection
 @pytest.mark.training
 @pytest.mark.detection_training
 @pytest.mark.detection_transfer_learning
 @pytest.mark.yolov3
-def test_detection_training():
+def test_detection_training(clear_keras_session):
 
-    try:
-        keras.backend.clear_session()
-    except:
-        None
 
     trainer = DetectionModelTrainer()
     trainer.setModelTypeAsYOLOv3()

test/test_image_recognition.py

@@ -7,13 +7,13 @@
 
 main_folder = os.getcwd()
 
+
+
+
 @pytest.mark.squeezenet
 @pytest.mark.recognition
 def test_recognition_model_squeezenet():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
 
     predictor = ImagePrediction()
     predictor.setModelTypeAsSqueezeNet()
@@ -29,10 +29,7 @@ def test_recognition_model_squeezenet():
 @pytest.mark.resnet
 @pytest.mark.recognition
 def test_recognition_model_resnet():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsResNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "resnet50_weights_tf_dim_ordering_tf_kernels.h5"))
@@ -47,10 +44,7 @@ def test_recognition_model_resnet():
 @pytest.mark.inceptionv3
 @pytest.mark.recognition
 def test_recognition_model_inceptionv3():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsInceptionV3()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "inception_v3_weights_tf_dim_ordering_tf_kernels.h5"))
@@ -65,10 +59,7 @@ def test_recognition_model_inceptionv3():
 @pytest.mark.densenet
 @pytest.mark.recognition
 def test_recognition_model_densenet():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsDenseNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "DenseNet-BC-121-32.h5"))
@@ -85,10 +76,6 @@ def test_recognition_model_densenet():
 @pytest.mark.recognition
 def test_recognition_model_squeezenet_array_input():
 
-    try:
-        keras.backend.clear_session()
-    except:
-        None
 
     predictor = ImagePrediction()
     predictor.setModelTypeAsSqueezeNet()
@@ -105,10 +92,7 @@ def test_recognition_model_squeezenet_array_input():
 @pytest.mark.resnet
 @pytest.mark.recognition
 def test_recognition_model_resnet_array_input():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsResNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "resnet50_weights_tf_dim_ordering_tf_kernels.h5"))
@@ -124,10 +108,7 @@ def test_recognition_model_resnet_array_input():
 @pytest.mark.inceptionv3
 @pytest.mark.recognition
 def test_recognition_model_inceptionv3_array_input():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsInceptionV3()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "inception_v3_weights_tf_dim_ordering_tf_kernels.h5"))
@@ -143,10 +124,7 @@ def test_recognition_model_inceptionv3_array_input():
 @pytest.mark.densenet
 @pytest.mark.recognition
 def test_recognition_model_densenet_array_input():
-    try:
-        keras.backend.clear_session()
-    except:
-        None
+
     predictor = ImagePrediction()
     predictor.setModelTypeAsDenseNet()
     predictor.setModelPath(os.path.join(main_folder, "data-models", "DenseNet-BC-121-32.h5"))
@@ -159,4 +137,3 @@ def test_recognition_model_densenet_array_input():
     assert isinstance(predictions[0], str)
     assert isinstance(probabilities[0], float)
 
-test_recognition_model_squeezenet()