更换文档检测模型

paddle_detection/configs/ssd/README.md

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+# SSD: Single Shot MultiBox Detector
+
+## Model Zoo
+
+### SSD on Pascal VOC
+
+| 骨架网络        | 网络类型       | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP |                           下载                          | 配置文件 |
+| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
+| VGG             | SSD            |    8    |   240e    |     ----     |  77.8  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_vgg16_300_240e_voc.yml) |
+| MobileNet v1    | SSD            |    32    |   120e    |     ----     |  73.8  | [下载链接](https://paddledet.bj.bcebos.com/models/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml) |
+
+**注意：** SSD-VGG使用4GPU在总batch size为32下训练240个epoch。SSD-MobileNetv1使用2GPU在总batch size为64下训练120周期。
+
+## Citations
+```
+@article{Liu_2016,
+   title={SSD: Single Shot MultiBox Detector},
+   journal={ECCV},
+   author={Liu, Wei and Anguelov, Dragomir and Erhan, Dumitru and Szegedy, Christian and Reed, Scott and Fu, Cheng-Yang and Berg, Alexander C.},
+   year={2016},
+}
+```

paddle_detection/configs/ssd/_base_/optimizer_120e.yml

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+epoch: 120
+
+LearningRate:
+  base_lr: 0.001
+  schedulers:
+  - !PiecewiseDecay
+    milestones: [40, 60, 80, 100]
+    gamma: [0.5, 0.5, 0.4, 0.1]
+    use_warmup: false
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.0
+    type: RMSProp
+  regularizer:
+    factor: 0.00005
+    type: L2

paddle_detection/configs/ssd/_base_/optimizer_1700e.yml

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+epoch: 1700
+
+LearningRate:
+  base_lr: 0.4
+  schedulers:
+  - !CosineDecay
+    max_epochs: 1700
+  - !LinearWarmup
+    start_factor: 0.3333333333333333
+    steps: 2000
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0005
+    type: L2

paddle_detection/configs/ssd/_base_/optimizer_240e.yml

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+epoch: 240
+
+LearningRate:
+  base_lr: 0.001
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones:
+    - 160
+    - 200
+  - !LinearWarmup
+    start_factor: 0.3333333333333333
+    steps: 500
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0005
+    type: L2

paddle_detection/configs/ssd/_base_/optimizer_70e.yml

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+epoch: 70
+
+LearningRate:
+  base_lr: 0.05
+  schedulers:
+  - !PiecewiseDecay
+    milestones: [48, 60]
+    gamma: [0.1, 0.1]
+    use_warmup: false
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0005
+    type: L2

paddle_detection/configs/ssd/_base_/ssd_mobilenet_reader.yml

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+worker_num: 8
+TrainReader:
+  inputs_def:
+    num_max_boxes: 90
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {brightness: [0.5, 1.125, 0.875], random_apply: False}
+    - RandomExpand: {fill_value: [127.5, 127.5, 127.5]}
+    - RandomCrop: {allow_no_crop: False}
+    - RandomFlip: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeBox: {}
+    - PadBox: {num_max_boxes: 90}
+  batch_transforms:
+    - NormalizeImage: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
+    - Permute: {}
+  batch_size: 32
+  shuffle: true
+  drop_last: true
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
+    - Permute: {}
+  batch_size: 1
+
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 300, 300]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
+    - Permute: {}
+  batch_size: 1

paddle_detection/configs/ssd/_base_/ssd_mobilenet_v1_300.yml

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+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ssd_mobilenet_v1_coco_pretrained.pdparams
+
+SSD:
+  backbone: MobileNet
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+
+MobileNet:
+  norm_decay: 0.
+  scale: 1
+  conv_learning_rate: 0.1
+  extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
+  with_extra_blocks: true
+  feature_maps: [11, 13, 14, 15, 16, 17]
+
+SSDHead:
+  kernel_size: 1
+  padding: 0
+  anchor_generator:
+    steps: [0, 0, 0, 0, 0, 0]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
+    min_ratio: 20
+    max_ratio: 90
+    base_size: 300
+    min_sizes: [60.0, 105.0, 150.0, 195.0, 240.0, 285.0]
+    max_sizes: [[], 150.0, 195.0, 240.0, 285.0, 300.0]
+    offset: 0.5
+    flip: true
+    min_max_aspect_ratios_order: false
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/_base_/ssd_r34_300.yml

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+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams
+
+SSD:
+  backbone: ResNet
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+  r34_backbone: True
+
+ResNet:
+  # index 0 stands for res2
+  depth: 34
+  norm_type: bn
+  freeze_norm: False
+  freeze_at: -1
+  return_idx: [2]
+  num_stages: 3
+
+SSDHead:
+  anchor_generator:
+    steps: [8, 16, 32, 64, 100, 300]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2.], [2.]]
+    min_sizes: [21.0, 45.0, 99.0, 153.0, 207.0, 261.0]
+    max_sizes: [45.0, 99.0, 153.0, 207.0, 261.0, 315.0]
+    offset: 0.5
+    clip: True
+    min_max_aspect_ratios_order: True
+  use_extra_head: True
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.05
+    nms_threshold: 0.5
+    nms_top_k: 400

paddle_detection/configs/ssd/_base_/ssd_r34_reader.yml

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+worker_num: 3
+TrainReader:
+  inputs_def:
+    num_max_boxes: 90
+  sample_transforms:
+    - Decode: {}
+    - RandomCrop: {num_attempts: 1}
+    - RandomFlip: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - RandomDistort: {brightness: [0.875, 1.125, 0.5], random_apply: False}
+    - NormalizeBox: {}
+    - PadBox: {num_max_boxes: 90}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 64
+  shuffle: true
+  drop_last: true
+  use_shared_memory: true
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1
+
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 300, 300]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1

paddle_detection/configs/ssd/_base_/ssd_reader.yml

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+worker_num: 2
+TrainReader:
+  inputs_def:
+    num_max_boxes: 90
+
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {brightness: [0.5, 1.125, 0.875], random_apply: False}
+    - RandomExpand: {fill_value: [104., 117., 123.]}
+    - RandomCrop: {allow_no_crop: true}
+    - RandomFlip: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeBox: {}
+    - PadBox: {num_max_boxes: 90}
+
+  batch_transforms:
+    - NormalizeImage: {mean: [104., 117., 123.], std: [1., 1., 1.], is_scale: false}
+    - Permute: {}
+
+  batch_size: 8
+  shuffle: true
+  drop_last: true
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [104., 117., 123.], std: [1., 1., 1.], is_scale: false}
+    - Permute: {}
+  batch_size: 1
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 300, 300]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [104., 117., 123.], std: [1., 1., 1.], is_scale: false}
+    - Permute: {}
+  batch_size: 1

paddle_detection/configs/ssd/_base_/ssd_vgg16_300.yml

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+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/VGG16_caffe_pretrained.pdparams
+
+# Model Architecture
+SSD:
+  # model feat info flow
+  backbone: VGG
+  ssd_head: SSDHead
+  # post process
+  post_process: BBoxPostProcess
+
+VGG:
+  depth: 16
+  normalizations: [20., -1, -1, -1, -1, -1]
+
+SSDHead:
+  anchor_generator:
+    steps: [8, 16, 32, 64, 100, 300]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2.], [2.]]
+    min_ratio: 20
+    max_ratio: 90
+    min_sizes: [30.0, 60.0, 111.0, 162.0, 213.0, 264.0]
+    max_sizes: [60.0, 111.0, 162.0, 213.0, 264.0, 315.0]
+    offset: 0.5
+    flip: true
+    min_max_aspect_ratios_order: true
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/_base_/ssdlite300_reader.yml

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+worker_num: 8
+TrainReader:
+  inputs_def:
+    num_max_boxes: 90
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {brightness: [0.5, 1.125, 0.875], random_apply: False}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {allow_no_crop: Fasle}
+    - RandomFlip: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeBox: {}
+    - PadBox: {num_max_boxes: 90}
+  batch_transforms:
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 64
+  shuffle: true
+  drop_last: true
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1
+
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 300, 300]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [300, 300], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1

paddle_detection/configs/ssd/_base_/ssdlite320_reader.yml

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+worker_num: 8
+TrainReader:
+  inputs_def:
+    num_max_boxes: 90
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {brightness: [0.5, 1.125, 0.875], random_apply: False}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {allow_no_crop: Fasle}
+    - RandomFlip: {}
+    - Resize: {target_size: [320, 320], keep_ratio: False, interp: 1}
+    - NormalizeBox: {}
+    - PadBox: {num_max_boxes: 90}
+  batch_transforms:
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 64
+  shuffle: true
+  drop_last: true
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [320, 320], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1
+
+
+TestReader:
+  inputs_def:
+    image_shape: [3, 320, 320]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [320, 320], keep_ratio: False, interp: 1}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
+    - Permute: {}
+  batch_size: 1

paddle_detection/configs/ssd/_base_/ssdlite_ghostnet_320.yml

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+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/GhostNet_x1_3_ssld_pretrained.pdparams
+
+SSD:
+  backbone: GhostNet
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+
+GhostNet:
+  scale: 1.3
+  conv_decay: 0.00004
+  with_extra_blocks: true
+  extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
+  feature_maps: [13, 18, 19, 20, 21, 22]
+  lr_mult_list: [0.25, 0.25, 0.5, 0.5, 0.75]
+
+SSDHead:
+  use_sepconv: True
+  conv_decay: 0.00004
+  anchor_generator:
+    steps: [16, 32, 64, 107, 160, 320]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
+    min_ratio: 20
+    max_ratio: 95
+    base_size: 320
+    min_sizes: []
+    max_sizes: []
+    offset: 0.5
+    flip: true
+    clip: true
+    min_max_aspect_ratios_order: false
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/_base_/ssdlite_mobilenet_v1_300.yml

@@ -0,0 +1,41 @@
+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_ssld_pretrained.pdparams
+
+SSD:
+  backbone: MobileNet
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+
+MobileNet:
+  conv_decay: 0.00004
+  scale: 1
+  extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
+  with_extra_blocks: true
+  feature_maps: [11, 13, 14, 15, 16, 17]
+
+SSDHead:
+  use_sepconv: True
+  conv_decay: 0.00004
+  anchor_generator:
+    steps: [16, 32, 64, 100, 150, 300]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
+    min_ratio: 20
+    max_ratio: 95
+    base_size: 300
+    min_sizes: []
+    max_sizes: []
+    offset: 0.5
+    flip: true
+    clip: true
+    min_max_aspect_ratios_order: False
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/_base_/ssdlite_mobilenet_v3_large_320.yml

@@ -0,0 +1,44 @@
+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
+
+SSD:
+  backbone: MobileNetV3
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+
+MobileNetV3:
+  scale: 1.0
+  model_name: large
+  conv_decay: 0.00004
+  with_extra_blocks: true
+  extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
+  feature_maps: [14, 17, 18, 19, 20, 21]
+  lr_mult_list: [0.25, 0.25, 0.5, 0.5, 0.75]
+  multiplier: 0.5
+
+SSDHead:
+  use_sepconv: True
+  conv_decay: 0.00004
+  anchor_generator:
+    steps: [16, 32, 64, 107, 160, 320]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
+    min_ratio: 20
+    max_ratio: 95
+    base_size: 320
+    min_sizes: []
+    max_sizes: []
+    offset: 0.5
+    flip: true
+    clip: true
+    min_max_aspect_ratios_order: false
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/_base_/ssdlite_mobilenet_v3_small_320.yml

@@ -0,0 +1,44 @@
+architecture: SSD
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams
+
+SSD:
+  backbone: MobileNetV3
+  ssd_head: SSDHead
+  post_process: BBoxPostProcess
+
+MobileNetV3:
+  scale: 1.0
+  model_name: small
+  conv_decay: 0.00004
+  with_extra_blocks: true
+  extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
+  feature_maps: [10, 13, 14, 15, 16, 17]
+  lr_mult_list: [0.25, 0.25, 0.5, 0.5, 0.75]
+  multiplier: 0.5
+
+SSDHead:
+  use_sepconv: True
+  conv_decay: 0.00004
+  anchor_generator:
+    steps: [16, 32, 64, 107, 160, 320]
+    aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
+    min_ratio: 20
+    max_ratio: 95
+    base_size: 320
+    min_sizes: []
+    max_sizes: []
+    offset: 0.5
+    flip: true
+    clip: true
+    min_max_aspect_ratios_order: false
+
+BBoxPostProcess:
+  decode:
+    name: SSDBox
+  nms:
+    name: MultiClassNMS
+    keep_top_k: 200
+    score_threshold: 0.01
+    nms_threshold: 0.45
+    nms_top_k: 400
+    nms_eta: 1.0

paddle_detection/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml

@@ -0,0 +1,14 @@
+_BASE_: [
+  '../datasets/voc.yml',
+  '../runtime.yml',
+  '_base_/optimizer_120e.yml',
+  '_base_/ssd_mobilenet_v1_300.yml',
+  '_base_/ssd_mobilenet_reader.yml',
+]
+weights: output/ssd_mobilenet_v1_300_120e_voc/model_final
+
+# set collate_batch to false because ground-truth info is needed
+# on voc dataset and should not collate data in batch when batch size
+# is larger than 1.
+EvalReader:
+  collate_batch: false

paddle_detection/configs/ssd/ssd_r34_70e_coco.yml

@@ -0,0 +1,11 @@
+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/optimizer_70e.yml',
+  '_base_/ssd_r34_300.yml',
+  '_base_/ssd_r34_reader.yml',
+]
+weights: output/ssd_r34_70e_coco/model_final
+
+log_iter: 100
+snapshot_epoch: 5

paddle_detection/configs/ssd/ssd_vgg16_300_240e_voc.yml

@@ -0,0 +1,14 @@
+_BASE_: [
+  '../datasets/voc.yml',
+  '../runtime.yml',
+  '_base_/optimizer_240e.yml',
+  '_base_/ssd_vgg16_300.yml',
+  '_base_/ssd_reader.yml',
+]
+weights: output/ssd_vgg16_300_240e_voc/model_final
+
+# set collate_batch to false because ground-truth info is needed
+# on voc dataset and should not collate data in batch when batch size
+# is larger than 1.
+EvalReader:
+  collate_batch: false

paddle_detection/configs/ssd/ssdlite_ghostnet_320_coco.yml

@@ -0,0 +1,27 @@
+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/optimizer_1700e.yml',
+  '_base_/ssdlite_ghostnet_320.yml',
+  '_base_/ssdlite320_reader.yml',
+]
+weights: output/ssdlite_ghostnet_320_coco/model_final
+
+epoch: 1700
+
+LearningRate:
+  base_lr: 0.2
+  schedulers:
+  - !CosineDecay
+    max_epochs: 1700
+  - !LinearWarmup
+    start_factor: 0.33333
+    steps: 2000
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0005
+    type: L2

paddle_detection/configs/ssd/ssdlite_mobilenet_v1_300_coco.yml

@@ -0,0 +1,8 @@
+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/optimizer_1700e.yml',
+  '_base_/ssdlite_mobilenet_v1_300.yml',
+  '_base_/ssdlite300_reader.yml',
+]
+weights: output/ssdlite_mobilenet_v1_300_coco/model_final

paddle_detection/configs/ssd/ssdlite_mobilenet_v3_large_320_coco.yml

@@ -0,0 +1,8 @@
+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/optimizer_1700e.yml',
+  '_base_/ssdlite_mobilenet_v3_large_320.yml',
+  '_base_/ssdlite320_reader.yml',
+]
+weights: output/ssdlite_mobilenet_v3_large_320_coco/model_final

paddle_detection/configs/ssd/ssdlite_mobilenet_v3_small_320_coco.yml

@@ -0,0 +1,8 @@
+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/optimizer_1700e.yml',
+  '_base_/ssdlite_mobilenet_v3_small_320.yml',
+  '_base_/ssdlite320_reader.yml',
+]
+weights: output/ssdlite_mobilenet_v3_small_320_coco/model_final