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PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/configs.py

+#================================================================
+#
+#   File name   : configs.py
+#   Author      : PyLessons
+#   Created date: 2020-08-18
+#   Website     : https://pylessons.com/
+#   GitHub      : https://github.com/pythonlessons/TensorFlow-2.x-YOLOv3
+#   Description : yolov3 configuration file
+#
+#================================================================
+
+# YOLO options
+YOLO_TYPE                   = "yolov3" # yolov4 or yolov3
+YOLO_FRAMEWORK              = "tf" # "tf" or "trt"
+YOLO_V3_WEIGHTS             = "model_data/yolov3.weights"
+YOLO_V4_WEIGHTS             = "model_data/yolov4.weights"
+YOLO_V3_TINY_WEIGHTS        = "model_data/yolov3-tiny.weights"
+YOLO_V4_TINY_WEIGHTS        = "model_data/yolov4-tiny.weights"
+YOLO_TRT_QUANTIZE_MODE      = "INT8" # INT8, FP16, FP32
+YOLO_CUSTOM_WEIGHTS         = True # "checkpoints/yolov3_custom" # used in evaluate_mAP.py and custom model detection, if not using leave False
+                            # YOLO_CUSTOM_WEIGHTS also used with TensorRT and custom model detection
+YOLO_COCO_CLASSES           = "model_data/coco/coco.names"
+YOLO_STRIDES                = [8, 16, 32]
+YOLO_IOU_LOSS_THRESH        = 0.5
+YOLO_ANCHOR_PER_SCALE       = 3
+YOLO_MAX_BBOX_PER_SCALE     = 100
+YOLO_INPUT_SIZE             = 416
+if YOLO_TYPE                == "yolov4":
+    YOLO_ANCHORS            = [[[12,  16], [19,   36], [40,   28]],
+                               [[36,  75], [76,   55], [72,  146]],
+                               [[142,110], [192, 243], [459, 401]]]
+if YOLO_TYPE                == "yolov3":
+    YOLO_ANCHORS            = [[[10,  13], [16,   30], [33,   23]],
+                               [[30,  61], [62,   45], [59,  119]],
+                               [[116, 90], [156, 198], [373, 326]]]
+# Train options
+TRAIN_YOLO_TINY             = False
+TRAIN_SAVE_BEST_ONLY        = False # saves only best model according validation loss (True recommended)
+TRAIN_SAVE_CHECKPOINT       = False # saves all best validated checkpoints in training process (may require a lot disk space) (False recommended)
+#TRAIN_CLASSES              = "mnist/mnist.names"
+TRAIN_CLASSES               = "./model_data/cone.txt"
+#TRAIN_ANNOT_PATH           = "mnist/mnist_train.txt"
+TRAIN_ANNOT_PATH            = "./model_data/cone_train.txt"
+TRAIN_LOGDIR                = "log"
+TRAIN_CHECKPOINTS_FOLDER    = "checkpoints"
+TRAIN_MODEL_NAME            = f"{YOLO_TYPE}_custom"
+TRAIN_LOAD_IMAGES_TO_RAM    = True # With True faster training, but need more RAM
+TRAIN_BATCH_SIZE            = 4
+TRAIN_INPUT_SIZE            = 416
+TRAIN_DATA_AUG              = True
+TRAIN_TRANSFER              = True
+TRAIN_FROM_CHECKPOINT       = False # "checkpoints/yolov3_custom"
+TRAIN_LR_INIT               = 1e-4
+TRAIN_LR_END                = 1e-6
+TRAIN_WARMUP_EPOCHS         = 2
+TRAIN_EPOCHS                = 100
+
+# TEST options
+#TEST_ANNOT_PATH            = "mnist/mnist_test.txt"
+TEST_ANNOT_PATH             = "./model_data/cone_test.txt"
+TEST_BATCH_SIZE             = 4
+TEST_INPUT_SIZE             = 416
+TEST_DATA_AUG               = False
+TEST_DECTECTED_IMAGE_PATH   = ""
+TEST_SCORE_THRESHOLD        = 0.3
+TEST_IOU_THRESHOLD          = 0.45
+
+if TRAIN_YOLO_TINY:
+    YOLO_STRIDES            = [16, 32]    
+    # YOLO_ANCHORS            = [[[23, 27],  [37, 58],   [81,  82]], # this line can be uncommented for default coco weights
+    YOLO_ANCHORS            = [[[10, 14],  [23, 27],   [37, 58]],
+                               [[81,  82], [135, 169], [344, 319]]]