def test_detector():
detector = Detector(n_jobs=1)
assert detector['n_jobs'] == 1
assert type(detector) == Detector
# Test detect image
inputFname = os.path.join(get_test_data_path(), "input.jpg")
out = detector.detect_image(inputFname=inputFname)
assert type(out) == Fex
assert len(out) == 1
assert out.happiness.values[0] > 0
outputFname = os.path.join(get_test_data_path(), "output.csv")
out = detector.detect_image(inputFname=inputFname, outputFname=outputFname)
assert out
assert os.path.exists(outputFname)
out = pd.read_csv(outputFname)
assert out.happiness.values[0] > 0
# Test detect video
inputFname = os.path.join(get_test_data_path(), "input.mp4")
out = detector.detect_video(inputFname=inputFname)
assert len(out) == 72
outputFname = os.path.join(get_test_data_path(), "output.csv")
out = detector.detect_video(inputFname=inputFname, outputFname=outputFname)
assert out
assert os.path.exists(outputFname)
out = pd.read_csv(outputFname)
assert out.happiness.values.max() > 0
def test_detect_image():
# Test detect image
detector = Detector(n_jobs=1)
inputFname = os.path.join(get_test_data_path(), "input.jpg")
out = detector.detect_image(inputFname=inputFname)
assert type(out) == Fex
assert len(out) == 1
assert out.happiness.values[0] > 0
outputFname = os.path.join(get_test_data_path(), "output.csv")
out = detector.detect_image(inputFname=inputFname, outputFname=outputFname)
assert out
assert os.path.exists(outputFname)
out = pd.read_csv(outputFname)
assert out.happiness.values[0] > 0
def test_resmasknet():
inputFname = os.path.join(get_test_data_path(), "sampler0000.jpg")
detector1 = Detector(emotion_model="resmasknet")
out = detector1.detect_image(inputFname)
assert out.emotions()["neutral"].values > 0.5
def test_nofile():
with pytest.raises(FileNotFoundError):
inputFname = os.path.join(get_test_data_path(), "nosuchfile.jpg")
detector1 = Detector(emotion_model="svm")
out = detector1.detect_image(inputFname)
def test_emotionrf():
# Emotion RF models is not good
inputFname = os.path.join(get_test_data_path(), "input.jpg")
detector1 = Detector(emotion_model="rf")
out = detector1.detect_image(inputFname)
assert out.emotions()["happiness"].values > 0.0
def test_emotionsvm():
inputFname = os.path.join(get_test_data_path(), "input.jpg")
detector1 = Detector(emotion_model="svm")
out = detector1.detect_image(inputFname)
assert out.emotions()["happiness"].values > 0.5