提交 bb99cfb8 编写于 作者: G Guanghua Yu 提交者: GitHub

Revert "[Dygraph] Fix SSD-MobileNet (#2109)"

This reverts commit 5d7f09ed.
上级 5d7f09ed
......@@ -7,7 +7,7 @@
| 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 | ---- | 78.2 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/ssd_vgg16_300_240e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd_vgg16_300_240e_voc.yml) |
| MobileNet v1 | SSD | 32 | 120e | ---- | 73.3 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/ssd_mobilenet_v1_300_120e_voc.yml) |
| MobileNet v1 | SSD | 32 | 120e | ---- | 73.1 | [下载链接](https://paddlemodels.bj.bcebos.com/object_detection/dygraph/ssd_mobilenet_v1_300_120e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/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。
......
......@@ -10,8 +10,8 @@ LearningRate:
OptimizerBuilder:
optimizer:
momentum: 0.0
type: RMSProp
momentum: 0.9
type: Momentum
regularizer:
factor: 0.00005
factor: 0.0005
type: L2
......@@ -2,18 +2,21 @@ worker_num: 8
TrainReader:
inputs_def:
num_max_boxes: 90
sample_transforms:
- DecodeOp: {}
- RandomDistortOp: {brightness: [0.5, 1.125, 0.875], random_apply: False}
- RandomExpandOp: {fill_value: [127.5, 127.5, 127.5]}
- RandomCropOp: {allow_no_crop: Fasle}
- RandomFlipOp: {}
- ResizeOp: {target_size: [300, 300], keep_ratio: False, interp: 1}
- NormalizeBoxOp: {}
- ResizeImage: {target_size: 300, interp: 1, use_cv2: false}
- PadBoxOp: {num_max_boxes: 90}
batch_transforms:
- NormalizeImageOp: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
- Permute: {}
- Permute: {to_bgr: true}
batch_size: 32
shuffle: true
drop_last: true
......@@ -24,7 +27,7 @@ EvalReader:
- DecodeOp: {}
- ResizeOp: {target_size: [300, 300], keep_ratio: False, interp: 1}
- NormalizeImageOp: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
- Permute: {}
- Permute: {to_bgr: true}
batch_size: 1
drop_empty: false
......@@ -36,5 +39,5 @@ TestReader:
- DecodeOp: {}
- ResizeOp: {target_size: [300, 300], keep_ratio: False, interp: 1}
- NormalizeImageOp: {mean: [127.5, 127.5, 127.5], std: [127.502231, 127.502231, 127.502231], is_scale: false}
- Permute: {}
- Permute: {to_bgr: true}
batch_size: 1
......@@ -8,8 +8,8 @@ TrainReader:
- RandomExpandOp: {fill_value: [123.675, 116.28, 103.53]}
- RandomCropOp: {allow_no_crop: Fasle}
- RandomFlipOp: {}
- ResizeOp: {target_size: [300, 300], keep_ratio: False, interp: 1}
- NormalizeBoxOp: {}
- ResizeImage: {target_size: 300, interp: 1, use_cv2: false}
- PadBoxOp: {num_max_boxes: 90}
batch_transforms:
- NormalizeImageOp: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
......
......@@ -8,8 +8,8 @@ TrainReader:
- RandomExpandOp: {fill_value: [123.675, 116.28, 103.53]}
- RandomCropOp: {allow_no_crop: Fasle}
- RandomFlipOp: {}
- ResizeOp: {target_size: [320, 320], keep_ratio: False, interp: 1}
- NormalizeBoxOp: {}
- ResizeImage: {target_size: 320, interp: 1, use_cv2: false}
- PadBoxOp: {num_max_boxes: 90}
batch_transforms:
- NormalizeImageOp: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: true}
......
......@@ -28,13 +28,13 @@ logger = setup_logger(__name__)
# Global dictionary
TRT_MIN_SUBGRAPH = {
'YOLO': 3,
'SSD': 40,
'SSD': 3,
'RCNN': 40,
'RetinaNet': 40,
'EfficientDet': 40,
'Face': 3,
'TTFNet': 40,
'FCOS': 40,
'TTFNet': 3,
'FCOS': 3,
'SOLOv2': 60,
}
......
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