Test suite update - fix timeout issue

.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 -m recognition -v
+  - pytest -v
 after_success:
   - codecov
   - coverage

test/test_custom_recognition.py

@@ -68,72 +68,3 @@ def test_custom_recognition_model_densenet():
     assert isinstance(predictions[0], str)
     assert isinstance(probabilities[0], str)
 
-
-
-@pytest.mark.recognition
-@pytest.mark.resnet
-@pytest.mark.recognition_custom
-@pytest.mark.recognition_multi
-def test_custom_recognition_model_resnet_multi():
-
-    predictor = CustomImagePrediction()
-    predictor.setModelTypeAsResNet()
-    predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_resnet.h5"))
-    predictor.setJsonPath(model_json=os.path.join(main_folder, "data-json", "idenprof.json"))
-    predictor.loadModel(num_objects=10)
-    images_to_image_array()
-    result_array = predictor.predictMultipleImages(sent_images_array=all_images_array)
-
-    assert isinstance(result_array, list)
-    for result in result_array:
-        assert "predictions" in result
-        assert "percentage_probabilities" in result
-        assert isinstance(result["predictions"], list)
-        assert isinstance(result["percentage_probabilities"], list)
-        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
-def test_custom_recognition_full_model_resnet_multi():
-
-    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"))
-    predictor.loadFullModel(num_objects=10)
-    images_to_image_array()
-    result_array = predictor.predictMultipleImages(sent_images_array=all_images_array)
-
-    assert isinstance(result_array, list)
-    for result in result_array:
-        assert "predictions" in result
-        assert "percentage_probabilities" in result
-        assert isinstance(result["predictions"], list)
-        assert isinstance(result["percentage_probabilities"], list)
-        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
-def test_custom_recognition_model_densenet_multi():
-
-    predictor = CustomImagePrediction()
-    predictor.setModelTypeAsDenseNet()
-    predictor.setModelPath(os.path.join(main_folder, "data-models", "idenprof_densenet-0.763500.h5"))
-    predictor.setJsonPath(model_json=os.path.join(main_folder, "data-json", "idenprof.json"))
-    predictor.loadModel(num_objects=10)
-    images_to_image_array()
-    result_array = predictor.predictMultipleImages(sent_images_array=all_images_array)
-
-    assert isinstance(result_array, list)
-    for result in result_array:
-        assert "predictions" in result
-        assert "percentage_probabilities" in result
-        assert isinstance(result["predictions"], list)
-        assert isinstance(result["percentage_probabilities"], list)
-        assert isinstance(result["predictions"][0], str)
-        assert isinstance(result["percentage_probabilities"][0], str)