Created by: heavengate

expand ratio=2.0 & add ppyolo_2x_bs12.yml

• add ppyolo_2x_bs12.yml with training batch size as 12, which can be trained on 16G GPU, val mAP=45.1%, weights at https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x_bs12.pdparams
• decrease RandomExpand.ratio to 2.0 in ppyolo_reader.yml to reduce CPU memory usage, tested with ppyolo_2x_bs12.yml, RandomExpand.ratio 4.0 -> 2.0, mAP is 0.1% higher

1. RandomExpand.ratio = 4.0

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.450                                                
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.649                                                
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.490                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.268                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.482                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.599                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.340                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.577                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.626                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.417                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.669                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.785

2. RandomExpand.ratio = 2.0

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.451                                                
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.651                                                
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.491                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.269                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.482                                                
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.598                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.343                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.576                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.629                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.418                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.669                                                
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.784