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| # built-in dependencies | |
| import base64 | |
| import unittest | |
| # project dependencies | |
| from deepface.api.src.app import create_app | |
| from deepface.commons import logger as log | |
| logger = log.get_singletonish_logger() | |
| class TestVerifyEndpoint(unittest.TestCase): | |
| def setUp(self): | |
| app = create_app() | |
| app.config["DEBUG"] = True | |
| app.config["TESTING"] = True | |
| self.app = app.test_client() | |
| def test_tp_verify(self): | |
| data = { | |
| "img1_path": "dataset/img1.jpg", | |
| "img2_path": "dataset/img2.jpg", | |
| } | |
| response = self.app.post("/verify", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("verified") is not None | |
| assert result.get("model") is not None | |
| assert result.get("similarity_metric") is not None | |
| assert result.get("detector_backend") is not None | |
| assert result.get("distance") is not None | |
| assert result.get("threshold") is not None | |
| assert result.get("facial_areas") is not None | |
| assert result.get("verified") is True | |
| logger.info("✅ true-positive verification api test is done") | |
| def test_tn_verify(self): | |
| data = { | |
| "img1_path": "dataset/img1.jpg", | |
| "img2_path": "dataset/img2.jpg", | |
| } | |
| response = self.app.post("/verify", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("verified") is not None | |
| assert result.get("model") is not None | |
| assert result.get("similarity_metric") is not None | |
| assert result.get("detector_backend") is not None | |
| assert result.get("distance") is not None | |
| assert result.get("threshold") is not None | |
| assert result.get("facial_areas") is not None | |
| assert result.get("verified") is True | |
| logger.info("✅ true-negative verification api test is done") | |
| def test_represent(self): | |
| data = { | |
| "img": "dataset/img1.jpg", | |
| } | |
| response = self.app.post("/represent", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("results") is not None | |
| assert isinstance(result["results"], list) is True | |
| assert len(result["results"]) > 0 | |
| for i in result["results"]: | |
| assert i.get("embedding") is not None | |
| assert isinstance(i.get("embedding"), list) is True | |
| assert len(i.get("embedding")) == 4096 | |
| assert i.get("face_confidence") is not None | |
| assert i.get("facial_area") is not None | |
| logger.info("✅ representation api test is done (for image path)") | |
| def test_represent_encoded(self): | |
| image_path = "dataset/img1.jpg" | |
| with open(image_path, "rb") as image_file: | |
| encoded_string = "data:image/jpeg;base64," + \ | |
| base64.b64encode(image_file.read()).decode("utf8") | |
| data = { | |
| "model_name": "Facenet", | |
| "detector_backend": "mtcnn", | |
| "img": encoded_string | |
| } | |
| response = self.app.post("/represent", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("results") is not None | |
| assert isinstance(result["results"], list) is True | |
| assert len(result["results"]) > 0 | |
| for i in result["results"]: | |
| assert i.get("embedding") is not None | |
| assert isinstance(i.get("embedding"), list) is True | |
| assert len(i.get("embedding")) == 128 | |
| assert i.get("face_confidence") is not None | |
| assert i.get("facial_area") is not None | |
| logger.info("✅ representation api test is done (for encoded image)") | |
| def test_represent_url(self): | |
| data = { | |
| "model_name": "Facenet", | |
| "detector_backend": "mtcnn", | |
| "img": "https://github.com/serengil/deepface/blob/master/tests/dataset/couple.jpg?raw=true" | |
| } | |
| response = self.app.post("/represent", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("results") is not None | |
| assert isinstance(result["results"], list) is True | |
| assert len(result["results"]) == 2 # 2 faces are in the image link | |
| for i in result["results"]: | |
| assert i.get("embedding") is not None | |
| assert isinstance(i.get("embedding"), list) is True | |
| assert len(i.get("embedding")) == 128 | |
| assert i.get("face_confidence") is not None | |
| assert i.get("facial_area") is not None | |
| logger.info("✅ representation api test is done (for image url)") | |
| def test_analyze(self): | |
| data = { | |
| "img": "dataset/img1.jpg", | |
| } | |
| response = self.app.post("/analyze", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| logger.debug(result) | |
| assert result.get("results") is not None | |
| assert isinstance(result["results"], list) is True | |
| assert len(result["results"]) > 0 | |
| for i in result["results"]: | |
| assert i.get("age") is not None | |
| assert isinstance(i.get("age"), (int, float)) | |
| assert i.get("dominant_gender") is not None | |
| assert i.get("dominant_gender") in ["Man", "Woman"] | |
| assert i.get("dominant_emotion") is not None | |
| assert i.get("dominant_race") is not None | |
| logger.info("✅ analyze api test is done") | |
| def test_analyze_inputformats(self): | |
| image_path = "dataset/couple.jpg" | |
| with open(image_path, "rb") as image_file: | |
| encoded_image = "data:image/jpeg;base64," + \ | |
| base64.b64encode(image_file.read()).decode("utf8") | |
| image_sources = [ | |
| # image path | |
| image_path, | |
| # image url | |
| f"https://github.com/serengil/deepface/blob/master/tests/{image_path}?raw=true", | |
| # encoded image | |
| encoded_image | |
| ] | |
| results = [] | |
| for img in image_sources: | |
| data = { | |
| "img": img, | |
| } | |
| response = self.app.post("/analyze", json=data) | |
| assert response.status_code == 200 | |
| result = response.json | |
| results.append(result) | |
| assert result.get("results") is not None | |
| assert isinstance(result["results"], list) is True | |
| assert len(result["results"]) > 0 | |
| for i in result["results"]: | |
| assert i.get("age") is not None | |
| assert isinstance(i.get("age"), (int, float)) | |
| assert i.get("dominant_gender") is not None | |
| assert i.get("dominant_gender") in ["Man", "Woman"] | |
| assert i.get("dominant_emotion") is not None | |
| assert i.get("dominant_race") is not None | |
| assert len(results[0]["results"]) == len(results[1]["results"])\ | |
| and len(results[0]["results"]) == len(results[2]["results"]) | |
| for i in range(len(results[0]['results'])): | |
| assert results[0]["results"][i]["dominant_emotion"] == results[1]["results"][i]["dominant_emotion"]\ | |
| and results[0]["results"][i]["dominant_emotion"] == results[2]["results"][i]["dominant_emotion"] | |
| assert results[0]["results"][i]["dominant_gender"] == results[1]["results"][i]["dominant_gender"]\ | |
| and results[0]["results"][i]["dominant_gender"] == results[2]["results"][i]["dominant_gender"] | |
| assert results[0]["results"][i]["dominant_race"] == results[1]["results"][i]["dominant_race"]\ | |
| and results[0]["results"][i]["dominant_race"] == results[2]["results"][i]["dominant_race"] | |
| logger.info("✅ different inputs test is done") | |
| def test_invalid_verify(self): | |
| data = { | |
| "img1_path": "dataset/invalid_1.jpg", | |
| "img2_path": "dataset/invalid_2.jpg", | |
| } | |
| response = self.app.post("/verify", json=data) | |
| assert response.status_code == 400 | |
| logger.info("✅ invalid verification request api test is done") | |
| def test_invalid_represent(self): | |
| data = { | |
| "img": "dataset/invalid_1.jpg", | |
| } | |
| response = self.app.post("/represent", json=data) | |
| assert response.status_code == 400 | |
| logger.info("✅ invalid represent request api test is done") | |
| def test_invalid_analyze(self): | |
| data = { | |
| "img": "dataset/invalid.jpg", | |
| } | |
| response = self.app.post("/analyze", json=data) | |
| assert response.status_code == 400 | |