From 3f29c6a606ca5fc0454595521c7c88ccb5aebbfe Mon Sep 17 00:00:00 2001 From: sasael Date: Sun, 12 Jun 2022 15:35:53 +0300 Subject: [PATCH] Added dominant_gender and probabilities for man / woman results in analyze function --- deepface/DeepFace.py | 23 ++++++++++++++++------- deepface/basemodels/ArcFace.py | 2 +- tests/test_nonbinary_gender.py | 32 ++++++++++++++++++++++++++++++++ tests/unit_tests.py | 10 +++++----- 4 files changed, 54 insertions(+), 13 deletions(-) create mode 100644 tests/test_nonbinary_gender.py diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py index 3394a5f..02f563a 100644 --- a/deepface/DeepFace.py +++ b/deepface/DeepFace.py @@ -294,7 +294,11 @@ def analyze(img_path, actions = ('emotion', 'age', 'gender', 'race') , models = { "region": {'x': 230, 'y': 120, 'w': 36, 'h': 45}, "age": 28.66, - "gender": "woman", + "dominant_gender": "Woman", + "gender": { + 'Woman': 99.99407529830933, + 'Man': 0.005928758764639497, + } "dominant_emotion": "neutral", "emotion": { 'sad': 37.65260875225067, @@ -417,14 +421,19 @@ def analyze(img_path, actions = ('emotion', 'age', 'gender', 'race') , models = if img_224 is None: img_224, region = functions.preprocess_face(img = img_path, target_size = (224, 224), grayscale = False, enforce_detection = enforce_detection, detector_backend = detector_backend, return_region = True) - gender_prediction = models['gender'].predict(img_224)[0,:] + gender_predictions = models['gender'].predict(img_224)[0,:] - if np.argmax(gender_prediction) == 0: - gender = "Woman" - elif np.argmax(gender_prediction) == 1: - gender = "Man" + sum_of_predictions = gender_predictions.sum() + gender_labels = ["Woman", "Man"] + resp_obj["gender"] = {} + + for i in range(0, len(gender_labels)): + gender_label = gender_labels[i] + gender_prediction = 100 * gender_predictions[i] / sum_of_predictions + resp_obj["gender"][gender_label] = gender_prediction + + resp_obj["dominant_gender"] = gender_labels[np.argmax(gender_predictions)] - resp_obj["gender"] = gender elif action == 'race': if img_224 is None: diff --git a/deepface/basemodels/ArcFace.py b/deepface/basemodels/ArcFace.py index 9aa9d4d..d6fb38d 100644 --- a/deepface/basemodels/ArcFace.py +++ b/deepface/basemodels/ArcFace.py @@ -23,7 +23,7 @@ def loadModel(url = 'https://github.com/serengil/deepface_models/releases/downlo arcface_model = keras.layers.Flatten()(arcface_model) arcface_model = keras.layers.Dense(512, activation=None, use_bias=True, kernel_initializer="glorot_normal")(arcface_model) embedding = keras.layers.BatchNormalization(momentum=0.9, epsilon=2e-5, name="embedding", scale=True)(arcface_model) - model = keras.models.Model(inputs, embedding, name=base_model.name) + model = keras.detectors.Model(inputs, embedding, name=base_model.name) #--------------------------------------- #check the availability of pre-trained weights diff --git a/tests/test_nonbinary_gender.py b/tests/test_nonbinary_gender.py new file mode 100644 index 0000000..6b2ff69 --- /dev/null +++ b/tests/test_nonbinary_gender.py @@ -0,0 +1,32 @@ +from deepface import DeepFace + +dataset = [ + 'dataset/img1.jpg', + 'dataset/img5.jpg', + 'dataset/img6.jpg', + 'dataset/img8.jpg', + 'dataset/img7.jpg', + 'dataset/img9.jpg', + 'dataset/img11.jpg', + 'dataset/img11.jpg', +] + +detectors = ['opencv', 'ssd', 'retinaface', 'mtcnn'] # dlib not tested + + +def test_gender_prediction(): + for detector in detectors: + results = DeepFace.analyze(dataset, actions=('gender',), detector_backend=detector, prog_bar=False) + for key in results.keys(): + result = results[key] + assert 'gender' in result.keys() + assert 'dominant_gender' in result.keys() and result["dominant_gender"] in ["Man", "Woman"] + if result["dominant_gender"] == "Man": + assert result["gender"]["Man"] > result["gender"]["Woman"] + else: + assert result["gender"]["Man"] < result["gender"]["Woman"] + print(f'detector {detector} passed') + + +if __name__ == "__main__": + test_gender_prediction() diff --git a/tests/unit_tests.py b/tests/unit_tests.py index 57a71de..84656c2 100644 --- a/tests/unit_tests.py +++ b/tests/unit_tests.py @@ -96,7 +96,7 @@ def test_cases(): print(demography) evaluate(demography["age"] > 20 and demography["age"] < 40) - evaluate(demography["gender"] == "Woman") + evaluate(demography["dominant_gender"] == "Woman") print("-----------------------------------------") @@ -108,12 +108,12 @@ def test_cases(): #check response is a valid json print("Age: ", demography["age"]) - print("Gender: ", demography["gender"]) + print("Gender: ", demography["dominant_gender"]) print("Race: ", demography["dominant_race"]) print("Emotion: ", demography["dominant_emotion"]) evaluate(demography.get("age") is not None) - evaluate(demography.get("gender") is not None) + evaluate(demography.get("dominant_gender") is not None) evaluate(demography.get("dominant_race") is not None) evaluate(demography.get("dominant_emotion") is not None) @@ -123,12 +123,12 @@ def test_cases(): demography = DeepFace.analyze(img, ['age', 'gender']) print("Age: ", demography.get("age")) - print("Gender: ", demography.get("gender")) + print("Gender: ", demography.get("dominant_gender")) print("Race: ", demography.get("dominant_race")) print("Emotion: ", demography.get("dominant_emotion")) evaluate(demography.get("age") is not None) - evaluate(demography.get("gender") is not None) + evaluate(demography.get("dominant_gender") is not None) evaluate(demography.get("dominant_race") is None) evaluate(demography.get("dominant_emotion") is None)