PaddleClas/docs/en/models/PPLCNet_en.md

PPLCNet series

Overview

The PPLCNet series is a network that has excellent performance on Intel-CPU proposed by the Baidu PaddleCV team. The author summarizes some methods that can improve the accuracy of the model on Intel-CPU but hardly increase the inference time. The author combines these methods into a new network, namely PPLCNet. Compared with other lightweight networks, PPLCNet can achieve higher accuracy with the same inference time. PPLCNet has shown strong competitiveness in image classification, object detection, and semantic segmentation.

Accuracy, FLOPS and Parameters

Models	Top1	Top5	FLOPs (M)	Parameters (M)
PPLCNet_x0_25	0.5186	0.7565	18	1.5
PPLCNet_x0_35	0.5809	0.8083	29	1.6
PPLCNet_x0_5	0.6314	0.8466	47	1.9
PPLCNet_x0_75	0.6818	0.8830	99	2.4
PPLCNet_x1_0	0.7132	0.9003	161	3.0
PPLCNet_x1_5	0.7371	0.9153	342	4.5
PPLCNet_x2_0	0.7518	0.9227	590	6.5
PPLCNet_x2_5	0.7660	0.9300	906	9.0
PPLCNet_x0_5_ssld	0.6610	0.8646	47	1.9
PPLCNet_x1_0_ssld	0.7439	0.9209	161	3.0
PPLCNet_x2_5_ssld	0.8082	0.9533	906	9.0

Inference speed based on Intel(R)-Xeon(R)-Gold-6148-CPU

Models	Crop Size	Resize Short Size	FP32 Batch Size=1 (ms)
PPLCNet_x0_25	224	256	1.74
PPLCNet_x0_35	224	256	1.92
PPLCNet_x0_5	224	256	2.05
PPLCNet_x0_75	224	256	2.29
PPLCNet_x1_0	224	256	2.46
PPLCNet_x1_5	224	256	3.19
PPLCNet_x2_0	224	256	4.27
PPLCNet_x2_5	224	256	5.39
PPLCNet_x0_5_ssld	224	256	2.05
PPLCNet_x1_0_ssld	224	256	2.46
PPLCNet_x2_5_ssld	224	256	5.39