Initial commit of project

config.py

@@ -0,0 +1,37 @@
+import os
+
+ENV = "dev"     # [dev/test/prod]
+
+PROJECT_DIR = os.path.dirname(os.path.abspath(__file__))
+print("PROJECT_DIR:\t", PROJECT_DIR)
+
+DATA_FOLDER = os.path.join(PROJECT_DIR, 'data')
+MODELS_FOLDER = os.path.join(PROJECT_DIR, 'models')
+LOGS_FOLDER = os.path.join(PROJECT_DIR, 'logs')
+
+if ENV == "dev":
+    print("DATA_FOLDER:\t", DATA_FOLDER)
+    print("MODELS_FOLDER:\t", MODELS_FOLDER)
+    print("LOGS_FOLDER:\t", LOGS_FOLDER)
+
+MODEL_WEIGHTS_PATH = os.path.join(MODELS_FOLDER, "bmi_model_weights.h5")
+GENDER_MODEL_PATH = os.path.join(MODELS_FOLDER, "simple_CNN.81-0.96.hdf5")
+AGE_TRAINED_MODEL_PATH = os.path.join(MODELS_FOLDER, "age_only_resnet50_weights.061-3.300-4.410.hdf5")
+CNN_FACE_DETECTOR_MODEL_PATH = os.path.join(MODELS_FOLDER, "mmod_human_face_detector.dat")
+BEAUTY_MODEL_WEIGHTS_PATH = os.path.join(MODELS_FOLDER, "beauty_model-ldl-resnet.h5")
+
+RESNET50_DEFAULT_IMG_WIDTH = 224
+MARGIN = .1
+TRAIN_BATCH_SIZE = 16
+VALIDATION_SIZE = 100
+
+ORIGINAL_IMGS_DIR = 'images'
+ORIGINAL_IMGS_INFO_FILE = 'data.csv'
+#AGE_TRAINED_WEIGHTS_FILE = 'age_only_resnet50_weights.061-3.300-4.410.hdf5'
+CROPPED_IMGS_DIR = 'normalized_images'
+CROPPED_IMGS_INFO_FILE = 'normalized_data.csv'
+TOP_LAYER_LOG_DIR = 'logs/top_layer'
+ALL_LAYERS_LOG_DIR = 'logs/all_layers'
+#The minimize percentage size of the targeted face to be considered for metadata extraction
+MIN_FACE_SIZE_PERCENTAGE = 0.05
+MIN_FACE_SIZE_PIXELS = (75 * 75)