Merge pull request #907 from serengil/feat-task-0612-logger

feat-task-654-use-custom-logger

Makefile

@@ -0,0 +1,5 @@
+test:
+	cd tests && python -m pytest unit_tests.py -s --disable-warnings
+
+lint:
+	python -m pylint deepface/ --fail-under=10

deepface/DeepFace.py

@@ -28,6 +28,9 @@
 )
 from deepface.extendedmodels import Age, Gender, Race, Emotion
 from deepface.commons import functions, realtime, distance as dst
+from deepface.commons.logger import Logger
+
+logger = Logger(module="DeepFace")
 
 # -----------------------------------
 # configurations for dependencies
@@ -340,7 +343,11 @@ def analyze(
         if img_content.shape[0] > 0 and img_content.shape[1] > 0:
             obj = {}
             # facial attribute analysis
-            pbar = tqdm(range(0, len(actions)), desc="Finding actions", disable=silent)
+            pbar = tqdm(
+                range(0, len(actions)),
+                desc="Finding actions",
+                disable=silent if len(actions) > 1 else True,
+            )
             for index in pbar:
                 action = actions[index]
                 pbar.set_description(f"Action: {action}")
@@ -461,17 +468,17 @@ def find(
     if path.exists(db_path + "/" + file_name):
 
         if not silent:
-            print(
-                f"WARNING: Representations for images in {db_path} folder were previously stored"
-                + f" in {file_name}. If you added new instances after the creation, then please "
-                + "delete this file and call find function again. It will create it again."
+            logger.warn(
+                f"Representations for images in {db_path} folder were previously stored"
+                f" in {file_name}. If you added new instances after the creation, then please "
+                "delete this file and call find function again. It will create it again."
             )
 
         with open(f"{db_path}/{file_name}", "rb") as f:
             representations = pickle.load(f)
 
         if not silent:
-            print("There are ", len(representations), " representations found in ", file_name)
+            logger.info(f"There are {len(representations)} representations found in {file_name}")
 
     else:  # create representation.pkl from scratch
         employees = []
@@ -539,7 +546,7 @@ def find(
             pickle.dump(representations, f)
 
         if not silent:
-            print(
+            logger.info(
                 f"Representations stored in {db_path}/{file_name} file."
                 + "Please delete this file when you add new identities in your database."
             )
@@ -614,7 +621,7 @@ def find(
     toc = time.time()
 
     if not silent:
-        print("find function lasts ", toc - tic, " seconds")
+        logger.info(f"find function lasts {toc - tic} seconds")
 
     return resp_obj
 
@@ -869,7 +876,7 @@ def detectFace(
             detected and aligned face as numpy array
 
     """
-    print("⚠️ Function detectFace is deprecated. Use extract_faces instead.")
+    logger.warn("Function detectFace is deprecated. Use extract_faces instead.")
     face_objs = extract_faces(
         img_path=img_path,
         target_size=target_size,

deepface/basemodels/ArcFace.py

@@ -2,6 +2,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.ArcFace")
 
 # pylint: disable=unsubscriptable-object
 
@@ -71,7 +74,7 @@ def loadModel(
 
     if os.path.isfile(output) != True:
 
-        print(file_name, " will be downloaded to ", output)
+        logger.info(f"{file_name} will be downloaded to {output}")
         gdown.download(url, output, quiet=False)
 
     # ---------------------------------------

deepface/basemodels/DeepID.py

@@ -2,6 +2,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.DeepID")
 
 tf_version = int(tf.__version__.split(".", maxsplit=1)[0])
 
@@ -71,7 +74,7 @@ def loadModel(
     home = functions.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/deepid_keras_weights.h5") != True:
-        print("deepid_keras_weights.h5 will be downloaded...")
+        logger.info("deepid_keras_weights.h5 will be downloaded...")
 
         output = home + "/.deepface/weights/deepid_keras_weights.h5"
         gdown.download(url, output, quiet=False)

deepface/basemodels/DlibResNet.py

@@ -3,6 +3,9 @@
 import gdown
 import numpy as np
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.DlibResNet")
 
 # pylint: disable=too-few-public-methods
 
@@ -24,7 +27,7 @@ def __init__(self):
 
         # download pre-trained model if it does not exist
         if os.path.isfile(weight_file) != True:
-            print("dlib_face_recognition_resnet_model_v1.dat is going to be downloaded")
+            logger.info("dlib_face_recognition_resnet_model_v1.dat is going to be downloaded")
 
             file_name = "dlib_face_recognition_resnet_model_v1.dat.bz2"
             url = f"http://dlib.net/files/{file_name}"

deepface/basemodels/Facenet.py

@@ -2,6 +2,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.Facenet")
 
 # --------------------------------
 # dependency configuration
@@ -1628,7 +1631,7 @@ def loadModel(
     home = functions.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/facenet_weights.h5") != True:
-        print("facenet_weights.h5 will be downloaded...")
+        logger.info("facenet_weights.h5 will be downloaded...")
 
         output = home + "/.deepface/weights/facenet_weights.h5"
         gdown.download(url, output, quiet=False)

deepface/basemodels/Facenet512.py

@@ -2,7 +2,9 @@
 import gdown
 from deepface.basemodels import Facenet
 from deepface.commons import functions
+from deepface.commons.logger import Logger
 
+logger = Logger(module="basemodels.Facenet512")
 
 def loadModel(
     url="https://github.com/serengil/deepface_models/releases/download/v1.0/facenet512_weights.h5",
@@ -15,7 +17,7 @@ def loadModel(
     home = functions.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/facenet512_weights.h5") != True:
-        print("facenet512_weights.h5 will be downloaded...")
+        logger.info("facenet512_weights.h5 will be downloaded...")
 
         output = home + "/.deepface/weights/facenet512_weights.h5"
         gdown.download(url, output, quiet=False)

deepface/basemodels/FbDeepFace.py

@@ -3,6 +3,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.FbDeepFace")
 
 # --------------------------------
 # dependency configuration
@@ -57,7 +60,7 @@ def loadModel(
     home = functions.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/VGGFace2_DeepFace_weights_val-0.9034.h5") != True:
-        print("VGGFace2_DeepFace_weights_val-0.9034.h5 will be downloaded...")
+        logger.info("VGGFace2_DeepFace_weights_val-0.9034.h5 will be downloaded...")
 
         output = home + "/.deepface/weights/VGGFace2_DeepFace_weights_val-0.9034.h5.zip"
 

deepface/basemodels/OpenFace.py

@@ -2,6 +2,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.OpenFace")
 
 tf_version = int(tf.__version__.split(".", maxsplit=1)[0])
 if tf_version == 1:
@@ -362,7 +365,7 @@ def loadModel(
     home = functions.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/openface_weights.h5") != True:
-        print("openface_weights.h5 will be downloaded...")
+        logger.info("openface_weights.h5 will be downloaded...")
 
         output = home + "/.deepface/weights/openface_weights.h5"
         gdown.download(url, output, quiet=False)

deepface/basemodels/SFace.py

@@ -4,6 +4,9 @@
 import gdown
 
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.SFace")
 
 # pylint: disable=line-too-long, too-few-public-methods
 
@@ -44,7 +47,7 @@ def load_model(
 
     if not os.path.isfile(file_name):
 
-        print("sface weights will be downloaded...")
+        logger.info("sface weights will be downloaded...")
 
         gdown.download(url, file_name, quiet=False)
 

deepface/basemodels/VGGFace.py

@@ -2,6 +2,9 @@
 import gdown
 import tensorflow as tf
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="basemodels.VGGFace")
 
 # ---------------------------------------
 
@@ -95,7 +98,7 @@ def loadModel(
     output = home + "/.deepface/weights/vgg_face_weights.h5"
 
     if os.path.isfile(output) != True:
-        print("vgg_face_weights.h5 will be downloaded...")
+        logger.info("vgg_face_weights.h5 will be downloaded...")
         gdown.download(url, output, quiet=False)
 
     # -----------------------------------

deepface/commons/functions.py

@@ -12,7 +12,9 @@
 
 # package dependencies
 from deepface.detectors import FaceDetector
+from deepface.commons.logger import Logger
 
+logger = Logger(module="commons.functions")
 
 # --------------------------------------------------
 # configurations of dependencies
@@ -41,11 +43,11 @@ def initialize_folder():
 
     if not os.path.exists(deepFaceHomePath):
         os.makedirs(deepFaceHomePath, exist_ok=True)
-        print("Directory ", home, "/.deepface created")
+        logger.info(f"Directory {home}/.deepface created")
 
     if not os.path.exists(weightsPath):
         os.makedirs(weightsPath, exist_ok=True)
-        print("Directory ", home, "/.deepface/weights created")
+        logger.info(f"Directory {home}/.deepface/weights created")
 
 
 def get_deepface_home():
@@ -115,6 +117,7 @@ def load_image(img):
     # This causes troubles when reading files with non english names
     # return cv2.imread(img)
 
+
 # --------------------------------------------------
 
 
@@ -357,7 +360,7 @@ def preprocess_face(
     Deprecated:
         0.0.78: Use extract_faces instead of preprocess_face.
     """
-    print("⚠️ Function preprocess_face is deprecated. Use extract_faces instead.")
+    logger.warn("Function preprocess_face is deprecated. Use extract_faces instead.")
     result = None
     img_objs = extract_faces(
         img=img,

deepface/commons/logger.py

@@ -0,0 +1,39 @@
+import os
+import logging
+
+# pylint: disable=broad-except
+class Logger:
+    def __init__(self, module=None):
+        self.module = module
+        log_level = os.environ.get("DEEPFACE_LOG_LEVEL", str(logging.INFO))
+        try:
+            self.log_level = int(log_level)
+        except Exception as err:
+            self.dump_log(
+                f"Exception while parsing $DEEPFACE_LOG_LEVEL."
+                f"Expected int but it is {log_level} ({str(err)})"
+            )
+            self.log_level = logging.INFO
+
+    def info(self, message):
+        if self.log_level <= logging.INFO:
+            self.dump_log(message)
+
+    def debug(self, message):
+        if self.log_level <= logging.DEBUG:
+            self.dump_log(f"🕷️ {message}")
+
+    def warn(self, message):
+        if self.log_level <= logging.WARNING:
+            self.dump_log(f"⚠️ {message}")
+
+    def error(self, message):
+        if self.log_level <= logging.ERROR:
+            self.dump_log(f"🔴 {message}")
+
+    def critical(self, message):
+        if self.log_level <= logging.CRITICAL:
+            self.dump_log(f"💥 {message}")
+
+    def dump_log(self, message):
+        print(message)

deepface/commons/realtime.py

@@ -5,6 +5,9 @@
 import cv2
 from deepface import DeepFace
 from deepface.commons import functions
+from deepface.commons.logger import Logger
+
+logger = Logger(module="commons.realtime")
 
 # dependency configuration
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
@@ -35,15 +38,15 @@ def analysis(
     # build models once to store them in the memory
     # otherwise, they will be built after cam started and this will cause delays
     DeepFace.build_model(model_name=model_name)
-    print(f"facial recognition model {model_name} is just built")
+    logger.info(f"facial recognition model {model_name} is just built")
 
     if enable_face_analysis:
         DeepFace.build_model(model_name="Age")
-        print("Age model is just built")
+        logger.info("Age model is just built")
         DeepFace.build_model(model_name="Gender")
-        print("Gender model is just built")
+        logger.info("Gender model is just built")
         DeepFace.build_model(model_name="Emotion")
-        print("Emotion model is just built")
+        logger.info("Emotion model is just built")
     # -----------------------
     # call a dummy find function for db_path once to create embeddings in the initialization
     DeepFace.find(
@@ -300,7 +303,7 @@ def analysis(
                                     apparent_age = demography["age"]
                                     dominant_gender = demography["dominant_gender"]
                                     gender = "M" if dominant_gender == "Man" else "W"
-                                    # print(f"{apparent_age} years old {dominant_emotion}")
+                                    logger.debug(f"{apparent_age} years old {dominant_gender}")
                                     analysis_report = str(int(apparent_age)) + " " + gender
 
                                     # -------------------------------
@@ -675,7 +678,7 @@ def analysis(
                                             1,
                                         )
                                 except Exception as err:  # pylint: disable=broad-except
-                                    print(str(err))
+                                    logger.error(str(err))
 
                         tic = time.time()  # in this way, freezed image can show 5 seconds
 

deepface/detectors/DlibWrapper.py

@@ -2,7 +2,9 @@
 import bz2
 import gdown
 from deepface.commons import functions
+from deepface.commons.logger import Logger
 
+logger = Logger(module="detectors.DlibWrapper")
 
 def build_model():
 
@@ -14,7 +16,7 @@ def build_model():
     if os.path.isfile(home + "/.deepface/weights/shape_predictor_5_face_landmarks.dat") != True:
 
         file_name = "shape_predictor_5_face_landmarks.dat.bz2"
-        print(f"{file_name} is going to be downloaded")
+        logger.info(f"{file_name} is going to be downloaded")
 
         url = f"http://dlib.net/files/{file_name}"
         output = f"{home}/.deepface/weights/{file_name}"