Merge pull request #1004 from serengil/feat-task-0402-api-bug-and-api-tests

Feat task 0402 api bug and api tests

Dockerfile

@@ -19,11 +19,8 @@ RUN apt-get install ffmpeg libsm6 libxext6 -y
 # -----------------------------------
 # Copy required files from repo into image
 COPY ./deepface /app/deepface
-COPY ./api/src/app.py /app/
-COPY ./api/src/api.py /app/
-COPY ./api/src/routes.py /app/
-COPY ./api/src/service.py /app/
 COPY ./requirements.txt /app/
+COPY ./package_info.json /app/package_info.json
 COPY ./setup.py /app/
 COPY ./README.md /app/
 
@@ -50,5 +47,6 @@ ENV PYTHONUNBUFFERED=1
 
 # -----------------------------------
 # run the app (re-configure port if necessary)
+WORKDIR /app/deepface/api/src
 EXPOSE 5000
 CMD ["gunicorn", "--workers=1", "--timeout=3600", "--bind=0.0.0.0:5000", "app:create_app()"]

README.md

@@ -280,7 +280,7 @@ user
 
 **API** - [`Demo`](https://youtu.be/HeKCQ6U9XmI)
 
-DeepFace serves an API as well. You can clone [`/api`](https://github.com/serengil/deepface/tree/master/api) folder and run the api via gunicorn server. This will get a rest service up. In this way, you can call deepface from an external system such as mobile app or web.
+DeepFace serves an API as well. You can clone deepface source code and run the api via gunicorn server with the following command. This will get a rest service up. In this way, you can call deepface from an external system such as mobile app or web.
 
 ```shell
 cd scripts

api/src/service.py

@@ -1,42 +0,0 @@
-from deepface import DeepFace
-
-
-def represent(img_path, model_name, detector_backend, enforce_detection, align):
-    result = {}
-    embedding_objs = DeepFace.represent(
-        img_path=img_path,
-        model_name=model_name,
-        detector_backend=detector_backend,
-        enforce_detection=enforce_detection,
-        align=align,
-    )
-    result["results"] = embedding_objs
-    return result
-
-
-def verify(
-    img1_path, img2_path, model_name, detector_backend, distance_metric, enforce_detection, align
-):
-    obj = DeepFace.verify(
-        img1_path=img1_path,
-        img2_path=img2_path,
-        model_name=model_name,
-        detector_backend=detector_backend,
-        distance_metric=distance_metric,
-        align=align,
-        enforce_detection=enforce_detection,
-    )
-    return obj
-
-
-def analyze(img_path, actions, detector_backend, enforce_detection, align):
-    result = {}
-    demographies = DeepFace.analyze(
-        img_path=img_path,
-        actions=actions,
-        detector_backend=detector_backend,
-        enforce_detection=enforce_detection,
-        align=align,
-    )
-    result["results"] = demographies
-    return result

deepface/api/src/app.py

@@ -1,7 +1,6 @@
 # 3rd parth dependencies
 from flask import Flask
-from routes import blueprint
-
+from deepface.api.src.modules.core.routes import blueprint
 
 def create_app():
     app = Flask(__name__)

deepface/api/src/modules/core/routes.py

@@ -1,5 +1,8 @@
 from flask import Blueprint, request
-import service
+from deepface.api.src.modules.core import service
+from deepface.commons.logger import Logger
+
+logger = Logger(module="api/src/routes.py")
 
 blueprint = Blueprint("routes", __name__)
 
@@ -16,7 +19,7 @@ def represent():
     if input_args is None:
         return {"message": "empty input set passed"}
 
-    img_path = input_args.get("img")
+    img_path = input_args.get("img") or input_args.get("img_path")
     if img_path is None:
         return {"message": "you must pass img_path input"}
 
@@ -33,6 +36,8 @@ def represent():
         align=align,
     )
 
+    logger.debug(obj)
+
     return obj
 
 
@@ -43,8 +48,8 @@ def verify():
     if input_args is None:
         return {"message": "empty input set passed"}
 
-    img1_path = input_args.get("img1_path")
-    img2_path = input_args.get("img2_path")
+    img1_path = input_args.get("img1") or input_args.get("img1_path")
+    img2_path = input_args.get("img2") or input_args.get("img2_path")
 
     if img1_path is None:
         return {"message": "you must pass img1_path input"}
@@ -68,7 +73,7 @@ def verify():
         enforce_detection=enforce_detection,
     )
 
-    verification["verified"] = str(verification["verified"])
+    logger.debug(verification)
 
     return verification
 
@@ -80,7 +85,7 @@ def analyze():
     if input_args is None:
         return {"message": "empty input set passed"}
 
-    img_path = input_args.get("img_path")
+    img_path = input_args.get("img") or input_args.get("img_path")
     if img_path is None:
         return {"message": "you must pass img_path input"}
 
@@ -97,4 +102,6 @@ def analyze():
         align=align,
     )
 
+    logger.debug(demographies)
+
     return demographies

deepface/api/src/modules/core/service.py

@@ -0,0 +1,54 @@
+from deepface import DeepFace
+
+# pylint: disable=broad-except
+
+
+def represent(img_path, model_name, detector_backend, enforce_detection, align):
+    try:
+        result = {}
+        embedding_objs = DeepFace.represent(
+            img_path=img_path,
+            model_name=model_name,
+            detector_backend=detector_backend,
+            enforce_detection=enforce_detection,
+            align=align,
+        )
+        result["results"] = embedding_objs
+        return result
+    except Exception as err:
+        return {"error": f"Exception while representing: {str(err)}"}, 400
+
+
+def verify(
+    img1_path, img2_path, model_name, detector_backend, distance_metric, enforce_detection, align
+):
+    try:
+        obj = DeepFace.verify(
+            img1_path=img1_path,
+            img2_path=img2_path,
+            model_name=model_name,
+            detector_backend=detector_backend,
+            distance_metric=distance_metric,
+            align=align,
+            enforce_detection=enforce_detection,
+        )
+        return obj
+    except Exception as err:
+        return {"error": f"Exception while verifying: {str(err)}"}, 400
+
+
+def analyze(img_path, actions, detector_backend, enforce_detection, align):
+    try:
+        result = {}
+        demographies = DeepFace.analyze(
+            img_path=img_path,
+            actions=actions,
+            detector_backend=detector_backend,
+            enforce_detection=enforce_detection,
+            align=align,
+            silent=True,
+        )
+        result["results"] = demographies
+        return result
+    except Exception as err:
+        return {"error": f"Exception while analyzing: {str(err)}"}, 400

deepface/modules/detection.py

@@ -167,10 +167,10 @@ def extract_faces(
             {
                 "face": img_pixels[:, :, ::-1] if human_readable is True else img_pixels,
                 "facial_area": {
-                    "x": current_region.x,
-                    "y": current_region.y,
-                    "w": current_region.w,
-                    "h": current_region.h,
+                    "x": int(current_region.x),
+                    "y": int(current_region.y),
+                    "w": int(current_region.w),
+                    "h": int(current_region.h),
                 },
                 "confidence": confidence,
             }

scripts/service.sh

@@ -1,3 +1,3 @@
 #!/usr/bin/env bash
-cd ../api/src
+cd ../deepface/api/src
 gunicorn --workers=1 --timeout=3600 --bind=0.0.0.0:5000 "app:create_app()"

tests/test_api.py

@@ -0,0 +1,123 @@
+import unittest
+from deepface.commons.logger import Logger
+from deepface.api.src.app import create_app
+
+
+logger = Logger("tests/test_api.py")
+
+
+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")
+
+    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_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