TensorRT-Demo/utils/yolo_classes.py

105 lines
1.9 KiB
Python

"""yolo_classes.py
NOTE: Number of YOLO COCO output classes differs from SSD COCO models.
"""
COCO_CLASSES_LIST = [
'person',
'bicycle',
'car',
'motorbike',
'aeroplane',
'bus',
'train',
'truck',
'boat',
'traffic light',
'fire hydrant',
'stop sign',
'parking meter',
'bench',
'bird',
'cat',
'dog',
'horse',
'sheep',
'cow',
'elephant',
'bear',
'zebra',
'giraffe',
'backpack',
'umbrella',
'handbag',
'tie',
'suitcase',
'frisbee',
'skis',
'snowboard',
'sports ball',
'kite',
'baseball bat',
'baseball glove',
'skateboard',
'surfboard',
'tennis racket',
'bottle',
'wine glass',
'cup',
'fork',
'knife',
'spoon',
'bowl',
'banana',
'apple',
'sandwich',
'orange',
'broccoli',
'carrot',
'hot dog',
'pizza',
'donut',
'cake',
'chair',
'sofa',
'pottedplant',
'bed',
'diningtable',
'toilet',
'tvmonitor',
'laptop',
'mouse',
'remote',
'keyboard',
'cell phone',
'microwave',
'oven',
'toaster',
'sink',
'refrigerator',
'book',
'clock',
'vase',
'scissors',
'teddy bear',
'hair drier',
'toothbrush',
]
# For translating YOLO class ids (0~79) to SSD class ids (0~90)
yolo_cls_to_ssd = [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20,
21, 22, 23, 24, 25, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 67, 70, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 84, 85, 86, 87, 88, 89, 90,
]
def get_cls_dict(category_num):
"""Get the class ID to name translation dictionary."""
if category_num == 80:
return {i: n for i, n in enumerate(COCO_CLASSES_LIST)}
else:
return {i: 'CLS%d' % i for i in range(category_num)}