--- comments: true --- # PaddleX Model List (Cambricon MLU) PaddleX incorporates multiple pipelines, each containing several modules, and each module encompasses various models. You can select the appropriate models based on the benchmark data below. If you prioritize model accuracy, choose models with higher accuracy. If you prioritize model size, select models with smaller storage requirements. ## Image Classification Module
Model Name Top-1 Accuracy (%) Model Storage Size (MB) Model Download Link
MobileNetV3_large_x0_5 69.2 9.6 Inference Model/Training Model
MobileNetV3_large_x0_35 64.3 7.5 Inference Model/Training Model
MobileNetV3_large_x0_75 73.1 14.0 Inference Model/Training Model
MobileNetV3_large_x1_0 75.3 19.5 Inference Model/Training Model
MobileNetV3_large_x1_25 76.4 26.5 Inference Model/Training Model
MobileNetV3_small_x0_5 59.2 6.8 Inference Model/Training Model
MobileNetV3_small_x0_35 53.0 6.0 Inference Model/Training Model
MobileNetV3_small_x0_75 66.0 8.5 Inference Model/Training Model
MobileNetV3_small_x1_0 68.2 10.5 Inference Model/Training Model
MobileNetV3_small_x1_25 70.7 13.0 Inference Model/Training Model
PP-HGNet_base 85.0 249.4 Inference Model/Training Model
PP-HGNet_small 81.51 86.5 Inference Model/Training Model
PP-HGNet_tiny 79.83 52.4 Inference Model/Training Model
PP-LCNet_x0_5 63.14 6.7 Inference Model/Training Model
PP-LCNet_x0_25 51.86 5.5 Inference Model/Training Model
PP-LCNet_x0_35 58.09 5.9 Inference Model/Training Model
PP-LCNet_x0_75 68.18 8.4 Inference Model/Training Model
PP-LCNet_x1_0 71.32 10.5 Inference Model/Training Model
PP-LCNet_x1_5 73.71 16.0 Inference Model/Training Model
PP-LCNet_x2_0 75.18 23.2 Inference Model/Training Model
PP-LCNet_x2_5 76.60 32.1 Inference Model/Training Model
ResNet18_vd 72.3 41.5 Inference Model/Training Model
ResNet18 71.0 41.5 Inference Model/Training Model
ResNet34_vd 76.0 77.3 Inference Model/Training Model
ResNet34 74.6 77.3 Inference Model/Training Model
ResNet50_vd 79.1 90.8 Inference Model/Training Model
ResNet50 76.5 90.8 Inference Model/Training Model
ResNet101_vd 80.2 158.4 Inference Model/Training Model
ResNet101 77.6 158.7 Inference Model/Training Model
ResNet152_vd 80.6 214.3 Inference Model/Training Model
ResNet152 78.3 214.2 Inference Model/Training Model
ResNet200_vd 80.9 266.0 Inference Model/Training Model
Note: The above accuracy metrics are Top-1 Accuracy on the [ImageNet-1k](https://www.image-net.org/index.php) validation set. ## Object Detection Module
Model Name mAP (%) Model Storage Size (MB) Model Download Link
PicoDet-L 42.6 20.9 Inference Model/Training Model
PicoDet-M 37.5 16.8 Inference Model/Training Model
PicoDet-S 29.1 4.4 Inference Model/Training Model
PicoDet-XS 26.2 5.7 Inference Model/Training Model
PP-YOLOE_plus-L 52.9 185.3 Inference Model/Training Model
PP-YOLOE_plus-M 49.8 83.2 Inference Model/Training Model
PP-YOLOE_plus-S 43.7 28.3 Inference Model/Training Model
PP-YOLOE_plus-X 54.7 349.4 Inference Model/Training Model
Note: The above accuracy metrics are mAP(0.5:0.95) on the [COCO2017](https://cocodataset.org/#home) validation set. ## [Semantic Segmentation Module](../module_usage/tutorials/cv_modules/semantic_segmentation.en.md)
Model Name mIoU (%) Model Storage Size (MB) Model Download Link
PP-LiteSeg-T 77.04 31 Inference Model/Training Model
Note: The above accuracy metrics are based on the mIoU of the [Cityscapes](https://www.cityscapes-dataset.com/) dataset. ## [Image Feature Module](../module_usage/tutorials/cv_modules/image_feature.en.md)
Model Name recall@1（%） Model Storage Size (MB) Model Download Link
PP-ShiTuV2_rec_CLIP_vit_base 88.69 306.6 Inference Model/Training Model
PP-ShiTuV2_rec_CLIP_vit_large 91.03 1050 Inference Model/Training Model
Note: The above accuracy metrics are for AliProducts recall@1。 ## [Abnormality Detection Module](../module_usage/tutorials/cv_modules/anomaly_detection.en.md)
Model Name Avg（%） Model Storage Size (MB) Model Download Link
STFPM 96.2 21.5 Inference Model/Training Model
Note: The above accuracy metrics are evaluated on the [MVTec AD](https://www.mvtec.com/company/research/datasets/mvtec-ad) dataset using the average anomaly score. ## [Face Detection Module](../module_usage/tutorials/cv_modules/face_detection.en.md)
Model Name AP (%)
Easy/Medium/Hard		 Model Storage Size (MB) Model Download Link
PicoDet_LCNet_x2_5_face 93.7/90.7/68.1 28.9 Inference Model/Training Model
Note: The above accuracy metrics are evaluated on the WIDER-FACE validation set with an input size of 640*640. ## Text Detection Module
Model Name Detection Hmean (%) Model Storage Size (MB) Model Download Link
PP-OCRv4_mobile_det 77.79 4.2 Inference Model/Training Model
PP-OCRv4_server_det 82.69 100.1 Inference Model/Training Model
Note: The evaluation set for the above accuracy metrics is PaddleOCR's self-built Chinese dataset, covering street scenes, web images, documents, handwriting, and more scenarios, with 500 images for detection. ## Text Recognition Module
Model Name Recognition Avg Accuracy (%) Model Storage Size (MB) Model Download Link
PP-OCRv4_mobile_rec 78.20 10.6 Inference Model/Training Model
PP-OCRv4_server_rec 79.20 71.2 Inference Model/Training Model
Note: The evaluation set for the above accuracy metrics is PaddleOCR's self-built Chinese dataset, covering street scenes, web images, documents, handwriting, and more scenarios, with 11,000 images for text recognition. ## Layout Analysis Module
Model Name mAP (%) Model Storage Size (MB) Model Download Link
PicoDet_layout_1x 86.8 7.4 Inference Model/Training Model
Note: The evaluation set for the above accuracy metrics is PaddleOCR's self-built layout analysis dataset, containing 10,000 images. ## [Time Series Forecasting Module](../module_usage/tutorials/time_series_modules/time_series_forecasting.en.md)
Model Name mse mae GPU Inference Time (ms)
[Normal Mode / High-Performance Mode]		 CPU Inference Time (ms)
[Normal Mode / High-Performance Mode]		 Model Storage Size (MB) Model Download Link
DLinear 0.382 0.394 0.34 / 0.12 0.64 / 0.06 0.072 Inference Model/Training Model
NLinear 0.386 0.392 0.27 / 0.10 0.49 / 0.08 0.04 Inference Model/Training Model
RLinear 0.385 0.392 0.39 / 0.18 0.82 / 0.08 0.04 Inference Model/Training Model
Note: The above accuracy metrics are measured on the [ETTH1](https://paddle-model-ecology.bj.bcebos.com/paddlex/data/Etth1.tar) dataset (evaluation results on the test set test.csv).