mindspore/model_zoo/official/cv/ssd/src/config.py

# Copyright 2020 Huawei Technologies Co., Ltd
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# distributed under the License is distributed on an "AS IS" BASIS,
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#" ============================================================================

"""Config parameters for SSD models."""

from easydict import EasyDict as ed

config = ed({
    "img_shape": [300, 300],
    "num_ssd_boxes": 1917,
    "neg_pre_positive": 3,
    "match_thershold": 0.5,
    "nms_thershold": 0.6,
    "min_score": 0.1,
    "max_boxes": 100,

    # learing rate settings
    "global_step": 0,
    "lr_init": 0.001,
    "lr_end_rate": 0.001,
    "warmup_epochs": 2,
    "momentum": 0.9,
    "weight_decay": 1.5e-4,

    # network
    "num_default": [3, 6, 6, 6, 6, 6],
    "extras_in_channels": [256, 576, 1280, 512, 256, 256],
    "extras_out_channels": [576, 1280, 512, 256, 256, 128],
    "extras_srides": [1, 1, 2, 2, 2, 2],
    "extras_ratio": [0.2, 0.2, 0.2, 0.25, 0.5, 0.25],
    "feature_size": [19, 10, 5, 3, 2, 1],
    "min_scale": 0.2,
    "max_scale": 0.95,
    "aspect_ratios": [(2,), (2, 3), (2, 3), (2, 3), (2, 3), (2, 3)],
    "steps": (16, 32, 64, 100, 150, 300),
    "prior_scaling": (0.1, 0.2),
    "gamma": 2.0,
    "alpha": 0.75,

    # `mindrecord_dir` and `coco_root` are better to use absolute path.
    "mindrecord_dir": "/data/MindRecord_COCO",
    "coco_root": "/data/coco2017",
    "train_data_type": "train2017",
    "val_data_type": "val2017",
    "instances_set": "annotations/instances_{}.json",
    "coco_classes": ('background', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', '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', 'couch', 'potted plant', 'bed',
                     'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote',
                     'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink',
                     'refrigerator', 'book', 'clock', 'vase', 'scissors',
                     'teddy bear', 'hair drier', 'toothbrush'),
    "num_classes": 81,
    # The annotation.json position of voc validation dataset.
    "voc_root": "",
    # voc original dataset.
    "voc_dir": "",
    # if coco or voc used, `image_dir` and `anno_path` are useless.
    "image_dir": "",
    "anno_path": "",
})