Loading... 文件名：ssd_mobilenet_v1_pets.config 路径：/path/to/models/research/object_detection/ models 下载地址：[Github - TensorFlow Models](https://github.com/tensorflow/models) ```json model { ssd { // 类别数，不包括 background num_classes: 20 // 原文:Scales location targets as used in paper for joint training box_coder { faster_rcnn_box_coder { y_scale: 10.0 x_scale: 10.0 height_scale: 5.0 width_scale: 5.0 } } // 匹配规则 matcher { argmax_matcher { matched_threshold: 0.5 unmatched_threshold: 0.5 ignore_thresholds: false negatives_lower_than_unmatched: true force_match_for_each_row: true } } // 区域相似度度量规则，原文 region_similarity_calculator similarity_calculator { iou_similarity {} } // 预测用的 defaut_boxes anchor_generator { ssd_anchor_generator { num_layers: 6 min_scale: 0.2 max_scale: 0.95 aspect_ratios: 1.0 aspect_ratios: 2.0 aspect_ratios: 0.5 aspect_ratios: 3.0 aspect_ratios: 0.3333 } } image_resizer { fixed_shape_resizer { // 输入图片高度 height: 300 // 输入图片宽度 width: 300 } } // 卷积预测层模块参数，原文 ssd_box_predictor box_predictor { convolutional_box_predictor { min_depth: 0 max_depth: 0 num_layers_before_predictor: 0 use_dropout: false dropout_keep_probability: 0.8 kernel_size: 1 box_code_size: 4 apply_sigmoid_to_scores: false conv_hyperparams { activation: RELU_6, regularizer { l2_regularizer { weight: 0.00004 } } initializer { truncated_normal_initializer { stddev: 0.03 mean: 0.0 } } batch_norm { train: true, scale: true, center: true, decay: 0.9997, epsilon: 0.001, } } } } // 特征提取 feature_extractor { type: 'ssd_mobilenet_v1' min_depth: 16 depth_multiplier: 1.0 conv_hyperparams { activation: RELU_6, regularizer { l2_regularizer { weight: 0.00004 } } initializer { truncated_normal_initializer { stddev: 0.03 mean: 0.0 } } batch_norm { train: true, scale: true, center: true, decay: 0.9997, epsilon: 0.001, } } } loss { // 损失函数 classification_loss { weighted_sigmoid {} } // 损失函数 localization_loss { weighted_smooth_l1 {} } // 难样本挖掘规则 hard_example_miner { num_hard_examples: 3000 iou_threshold: 0.99 loss_type: CLASSIFICATION max_negatives_per_positive: 3 min_negatives_per_image: 0 } classification_weight: 1.0 localization_weight: 1.0 } normalize_loss_by_num_matches: true post_processing { // 图像后处理，只用于验证，不参与训练流程 batch_non_max_suppression { score_threshold: 1e-8 iou_threshold: 0.6 max_detections_per_class: 100 max_total_detections: 100 } // 图像后处理，只用于验证，不参与训练流程 score_converter: SIGMOID } } } train_config: { // 每迭代一次输入的图片数量 batch_size: 16 optimizer { rms_prop_optimizer: { learning_rate: { exponential_decay_learning_rate { initial_learning_rate: 0.001 decay_steps: 40000 decay_factor: 0.1 } } momentum_optimizer_value: 0.9 decay: 0.005 epsilon: 1.0 } } fine_tune_checkpoint: "/usr/local/anaconda3/lib/python3.6/site-packages/tensorflow/models/research/object_detection/ssd_model/ssd_mobilenet/model.ckpt" from_detection_checkpoint: true load_all_detection_checkpoint_vars: true // 训练迭代次数 num_steps: 50200 data_augmentation_options { random_horizontal_flip {} } data_augmentation_options { ssd_random_crop {} } } train_input_reader: { tf_record_input_reader { input_path: "/usr/local/anaconda3/lib/python3.6/site-packages/tensorflow/models/research/object_detection/ssd_model/pascal_train.record" } label_map_path: "/usr/local/anaconda3/lib/python3.6/site-packages/tensorflow/models/research/object_detection/ssd_model/pascal_label_map.pbtxt" } eval_config: { metrics_set: "coco_detection_metrics" // 验证集中图片数量 num_examples: 1100 } eval_input_reader: { tf_record_input_reader { input_path: "/usr/local/anaconda3/lib/python3.6/site-packages/tensorflow/models/research/object_detection/ssd_model/pascal_val.record" } label_map_path: "/usr/local/anaconda3/lib/python3.6/site-packages/tensorflow/models/research/object_detection/ssd_model/pascal_label_map.pbtxt" shuffle: false num_readers: 1 } ``` 最后修改：2022 年 01 月 03 日 © 允许规范转载