From 4d79d66f1605a6618831ca256eb7eb7c08172f79 Mon Sep 17 00:00:00 2001 From: "mingjiang.li" Date: Thu, 17 Apr 2025 18:03:17 +0800 Subject: [PATCH] add 13 igie models to model list --- README.md | 14 +++++++++++++- README_en.md | 14 +++++++++++++- models/cv/object_detection/yolov12/igie/README.md | 2 +- 3 files changed, 27 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index f421dfd0..73019266 100644 --- a/README.md +++ b/README.md @@ -61,10 +61,12 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | ConvNeXt-Base | FP16 | [✅](models/cv/classification/convnext_base/igie) | [✅](models/cv/classification/convnext_base/ixrt) | 4.2.0 | | ConvNext-S | FP16 | [✅](models/cv/classification/convnext_s/igie) | | 4.2.0 | | ConvNeXt-Small | FP16 | [✅](models/cv/classification/convnext_small/igie) | [✅](models/cv/classification/convnext_small/ixrt) | 4.2.0 | +| ConvNeXt-Tiny | FP16 | [✅](models/cv/classification/convnext_tiny/igie) | | 4.2.0 | | CSPDarkNet53 | FP16 | [✅](models/cv/classification/cspdarknet53/igie) | [✅](models/cv/classification/cspdarknet53/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/cspdarknet53/ixrt) | 4.2.0 | | CSPResNet50 | FP16 | [✅](models/cv/classification/cspresnet50/igie) | [✅](models/cv/classification/cspresnet50/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/cspresnet50/ixrt) | 4.2.0 | +| CSPResNeXt50 | FP16 | [✅](models/cv/classification/cspresnext50/igie) | | 4.2.0 | | DeiT-tiny | FP16 | [✅](models/cv/classification/deit_tiny/igie) | [✅](models/cv/classification/deit_tiny/ixrt) | 4.2.0 | | DenseNet121 | FP16 | [✅](models/cv/classification/densenet121/igie) | [✅](models/cv/classification/densenet121/ixrt) | 4.2.0 | | DenseNet161 | FP16 | [✅](models/cv/classification/densenet161/igie) | [✅](models/cv/classification/densenet161/ixrt) | 4.2.0 | @@ -77,6 +79,7 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | EfficientNet-B2 | FP16 | [✅](models/cv/classification/efficientnet_b2/igie) | [✅](models/cv/classification/efficientnet_b2/ixrt) | 4.2.0 | | EfficientNet-B3 | FP16 | [✅](models/cv/classification/efficientnet_b3/igie) | [✅](models/cv/classification/efficientnet_b3/ixrt) | 4.2.0 | | EfficientNet-B4 | FP16 | [✅](models/cv/classification/efficientnet_b4/igie) | | 4.2.0 | +| EfficientNet-B5 | FP16 | [✅](models/cv/classification/efficientnet_b5/igie) | | 4.2.0 | | EfficientNetV2 | FP16 | [✅](models/cv/classification/efficientnet_v2/igie) | [✅](models/cv/classification/efficientnet_v2/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/efficientnet_v2/ixrt) | 4.2.0 | | EfficientNetv2_rw_t | FP16 | [✅](models/cv/classification/efficientnetv2_rw_t/igie) | [✅](models/cv/classification/efficientnetv2_rw_t/ixrt) | 4.2.0 | @@ -92,6 +95,7 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | Mixer_B | FP16 | [✅](models/cv/classification/mlp_mixer_base/igie) | | 4.2.0 | | MNASNet0_5 | FP16 | [✅](models/cv/classification/mnasnet0_5/igie) | | 4.2.0 | | MNASNet0_75 | FP16 | [✅](models/cv/classification/mnasnet0_75/igie) | | 4.2.0 | +| MNASNet1_0 | FP16 | [✅](models/cv/classification/mnasnet1_0/igie) | | 4.2.0 | | MobileNetV2 | FP16 | [✅](models/cv/classification/mobilenet_v2/igie) | [✅](models/cv/classification/mobilenet_v2/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/mobilenet_v2/igie) | [✅](models/cv/classification/mobilenet_v2/ixrt) | 4.2.0 | | MobileNetV3_Large | FP16 | [✅](models/cv/classification/mobilenet_v3_large/igie) | | 4.2.0 | @@ -99,7 +103,9 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | MViTv2_base | FP16 | [✅](models/cv/classification/mvitv2_base/igie) | | 4.2.0 | | RegNet_x_16gf | FP16 | [✅](models/cv/classification/regnet_x_16gf/igie) | | 4.2.0 | | RegNet_x_1_6gf | FP16 | [✅](models/cv/classification/regnet_x_1_6gf/igie) | | 4.2.0 | +| RegNet_x_3_2gf | FP16 | [✅](models/cv/classification/regnet_x_3_2gf/igie) | | 4.2.0 | | RegNet_y_1_6gf | FP16 | [✅](models/cv/classification/regnet_y_1_6gf/igie) | | 4.2.0 | +| RegNet_y_16gf | FP16 | [✅](models/cv/classification/regnet_y_16gf/igie) | | 4.2.0 | | RepVGG | FP16 | [✅](models/cv/classification/repvgg/igie) | [✅](models/cv/classification/repvgg/ixrt) | 4.2.0 | | Res2Net50 | FP16 | [✅](models/cv/classification/res2net50/igie) | [✅](models/cv/classification/res2net50/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/res2net50/ixrt) | 4.2.0 | @@ -127,14 +133,19 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | ShuffleNetV2_x2_0 | FP16 | [✅](models/cv/classification/shufflenetv2_x2_0/igie) | | 4.2.0 | | SqueezeNet 1.0 | FP16 | [✅](models/cv/classification/squeezenet_v1_0/igie) | [✅](models/cv/classification/squeezenet_v1_0/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/squeezenet_v1_0/ixrt) | 4.2.0 | -| SqueezeNet 1.1 | FP16 | | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | +| SqueezeNet 1.1 | FP16 | [✅](models/cv/classification/squeezenet_v1_1/igie) | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | | SVT Base | FP16 | [✅](models/cv/classification/svt_base/igie) | | 4.2.0 | | Swin Transformer | FP16 | [✅](models/cv/classification/swin_transformer/igie) | | 4.2.0 | | Swin Transformer Large | FP16 | | [✅](models/cv/classification/swin_transformer_large/ixrt) | 4.2.0 | +| Twins_PCPVT | FP16 | [✅](models/cv/classification/twins_pcpvt/igie) | | 4.2.0 | +| VAN_B0 | FP16 | [✅](models/cv/classification/van_b0/igie) | | 4.2.0 | | VGG11 | FP16 | [✅](models/cv/classification/vgg11/igie) | | 4.2.0 | | VGG16 | FP16 | [✅](models/cv/classification/vgg16/igie) | [✅](models/cv/classification/vgg16/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/vgg16/igie) | | 4.2.0 | +| VGG19 | FP16 | [✅](models/cv/classification/vgg19/igie) | | 4.2.0 | +| VGG19_BN | FP16 | [✅](models/cv/classification/vgg19_bn/igie) | | 4.2.0 | +| ViT | FP16 | [✅](models/cv/classification/vit/igie) | | 4.2.0 | | Wide ResNet50 | FP16 | [✅](models/cv/classification/wide_resnet50/igie) | [✅](models/cv/classification/wide_resnet50/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/wide_resnet50/igie) | [✅](models/cv/classification/wide_resnet50/ixrt) | 4.2.0 | | Wide ResNet101 | FP16 | [✅](models/cv/classification/wide_resnet101/igie) | | 4.2.0 | @@ -172,6 +183,7 @@ DeepSparkInference将按季度进行版本更新，后续会逐步丰富模型 | YOLOv9 | FP16 | [✅](models/cv/object_detection/yolov9/igie) | | 4.2.0 | | YOLOv10 | FP16 | [✅](models/cv/object_detection/yolov10/igie) | | 4.2.0 | | YOLOv11 | FP16 | [✅](models/cv/object_detection/yolov11/igie) | | 4.2.0 | +| YOLOv12 | FP16 | [✅](models/cv/object_detection/yolov12/igie) | | 4.2.0 | | YOLOX | FP16 | [✅](models/cv/object_detection/yolox/igie) | [✅](models/cv/object_detection/yolox/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/object_detection/yolox/igie) | [✅](models/cv/object_detection/yolox/ixrt) | 4.2.0 | diff --git a/README_en.md b/README_en.md index df4d7aba..9fd1d6ae 100644 --- a/README_en.md +++ b/README_en.md @@ -71,10 +71,12 @@ inference to be expanded in the future. | ConvNeXt-Base | FP16 | [✅](models/cv/classification/convnext_base/igie) | [✅](models/cv/classification/convnext_base/ixrt) | 4.2.0 | | ConvNext-S | FP16 | [✅](models/cv/classification/convnext_s/igie) | | 4.2.0 | | ConvNeXt-Small | FP16 | [✅](models/cv/classification/convnext_small/igie) | [✅](models/cv/classification/convnext_small/ixrt) | 4.2.0 | +| ConvNeXt-Tiny | FP16 | [✅](models/cv/classification/convnext_tiny/igie) | | 4.2.0 | | CSPDarkNet53 | FP16 | [✅](models/cv/classification/cspdarknet53/igie) | [✅](models/cv/classification/cspdarknet53/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/cspdarknet53/ixrt) | 4.2.0 | | CSPResNet50 | FP16 | [✅](models/cv/classification/cspresnet50/igie) | [✅](models/cv/classification/cspresnet50/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/cspresnet50/ixrt) | 4.2.0 | +| CSPResNeXt50 | FP16 | [✅](models/cv/classification/cspresnext50/igie) | | 4.2.0 | | DeiT-tiny | FP16 | [✅](models/cv/classification/deit_tiny/igie) | [✅](models/cv/classification/deit_tiny/ixrt) | 4.2.0 | | DenseNet121 | FP16 | [✅](models/cv/classification/densenet121/igie) | [✅](models/cv/classification/densenet121/ixrt) | 4.2.0 | | DenseNet161 | FP16 | [✅](models/cv/classification/densenet161/igie) | [✅](models/cv/classification/densenet161/ixrt) | 4.2.0 | @@ -87,6 +89,7 @@ inference to be expanded in the future. | EfficientNet-B2 | FP16 | [✅](models/cv/classification/efficientnet_b2/igie) | [✅](models/cv/classification/efficientnet_b2/ixrt) | 4.2.0 | | EfficientNet-B3 | FP16 | [✅](models/cv/classification/efficientnet_b3/igie) | [✅](models/cv/classification/efficientnet_b3/ixrt) | 4.2.0 | | EfficientNet-B4 | FP16 | [✅](models/cv/classification/efficientnet_b4/igie) | | 4.2.0 | +| EfficientNet-B5 | FP16 | [✅](models/cv/classification/efficientnet_b5/igie) | | 4.2.0 | | EfficientNetV2 | FP16 | [✅](models/cv/classification/efficientnet_v2/igie) | [✅](models/cv/classification/efficientnet_v2/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/efficientnet_v2/ixrt) | 4.2.0 | | EfficientNetv2_rw_t | FP16 | [✅](models/cv/classification/efficientnetv2_rw_t/igie) | [✅](models/cv/classification/efficientnetv2_rw_t/ixrt) | 4.2.0 | @@ -102,6 +105,7 @@ inference to be expanded in the future. | Mixer_B | FP16 | [✅](models/cv/classification/mlp_mixer_base/igie) | | 4.2.0 | | MNASNet0_5 | FP16 | [✅](models/cv/classification/mnasnet0_5/igie) | | 4.2.0 | | MNASNet0_75 | FP16 | [✅](models/cv/classification/mnasnet0_75/igie) | | 4.2.0 | +| MNASNet1_0 | FP16 | [✅](models/cv/classification/mnasnet1_0/igie) | | 4.2.0 | | MobileNetV2 | FP16 | [✅](models/cv/classification/mobilenet_v2/igie) | [✅](models/cv/classification/mobilenet_v2/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/mobilenet_v2/igie) | [✅](models/cv/classification/mobilenet_v2/ixrt) | 4.2.0 | | MobileNetV3_Large | FP16 | [✅](models/cv/classification/mobilenet_v3_large/igie) | | 4.2.0 | @@ -109,7 +113,9 @@ inference to be expanded in the future. | MViTv2_base | FP16 | [✅](models/cv/classification/mvitv2_base/igie) | | 4.2.0 | | RegNet_x_16gf | FP16 | [✅](models/cv/classification/regnet_x_16gf/igie) | | 4.2.0 | | RegNet_x_1_6gf | FP16 | [✅](models/cv/classification/regnet_x_1_6gf/igie) | | 4.2.0 | +| RegNet_x_3_2gf | FP16 | [✅](models/cv/classification/regnet_x_3_2gf/igie) | | 4.2.0 | | RegNet_y_1_6gf | FP16 | [✅](models/cv/classification/regnet_y_1_6gf/igie) | | 4.2.0 | +| RegNet_y_16gf | FP16 | [✅](models/cv/classification/regnet_y_16gf/igie) | | 4.2.0 | | RepVGG | FP16 | [✅](models/cv/classification/repvgg/igie) | [✅](models/cv/classification/repvgg/ixrt) | 4.2.0 | | Res2Net50 | FP16 | [✅](models/cv/classification/res2net50/igie) | [✅](models/cv/classification/res2net50/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/res2net50/ixrt) | 4.2.0 | @@ -137,14 +143,19 @@ inference to be expanded in the future. | ShuffleNetV2_x2_0 | FP16 | [✅](models/cv/classification/shufflenetv2_x2_0/igie) | | 4.2.0 | | SqueezeNet 1.0 | FP16 | [✅](models/cv/classification/squeezenet_v1_0/igie) | [✅](models/cv/classification/squeezenet_v1_0/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/squeezenet_v1_0/ixrt) | 4.2.0 | -| SqueezeNet 1.1 | FP16 | | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | +| SqueezeNet 1.1 | FP16 | [✅](models/cv/classification/squeezenet_v1_1/igie) | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | | | INT8 | | [✅](models/cv/classification/squeezenet_v1_1/ixrt) | 4.2.0 | | SVT Base | FP16 | [✅](models/cv/classification/svt_base/igie) | | 4.2.0 | | Swin Transformer | FP16 | [✅](models/cv/classification/swin_transformer/igie) | | 4.2.0 | | Swin Transformer Large | FP16 | | [✅](models/cv/classification/swin_transformer_large/ixrt) | 4.2.0 | +| Twins_PCPVT | FP16 | [✅](models/cv/classification/twins_pcpvt/igie) | | 4.2.0 | +| VAN_B0 | FP16 | [✅](models/cv/classification/van_b0/igie) | | 4.2.0 | | VGG11 | FP16 | [✅](models/cv/classification/vgg11/igie) | | 4.2.0 | | VGG16 | FP16 | [✅](models/cv/classification/vgg16/igie) | [✅](models/cv/classification/vgg16/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/vgg16/igie) | | 4.2.0 | +| VGG19 | FP16 | [✅](models/cv/classification/vgg19/igie) | | 4.2.0 | +| VGG19_BN | FP16 | [✅](models/cv/classification/vgg19_bn/igie) | | 4.2.0 | +| ViT | FP16 | [✅](models/cv/classification/vit/igie) | | 4.2.0 | | Wide ResNet50 | FP16 | [✅](models/cv/classification/wide_resnet50/igie) | [✅](models/cv/classification/wide_resnet50/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/classification/wide_resnet50/igie) | [✅](models/cv/classification/wide_resnet50/ixrt) | 4.2.0 | | Wide ResNet101 | FP16 | [✅](models/cv/classification/wide_resnet101/igie) | | 4.2.0 | @@ -182,6 +193,7 @@ inference to be expanded in the future. | YOLOv9 | FP16 | [✅](models/cv/object_detection/yolov9/igie) | | 4.2.0 | | YOLOv10 | FP16 | [✅](models/cv/object_detection/yolov10/igie) | | 4.2.0 | | YOLOv11 | FP16 | [✅](models/cv/object_detection/yolov11/igie) | | 4.2.0 | +| YOLOv12 | FP16 | [✅](models/cv/object_detection/yolov12/igie) | | 4.2.0 | | YOLOX | FP16 | [✅](models/cv/object_detection/yolox/igie) | [✅](models/cv/object_detection/yolox/ixrt) | 4.2.0 | | | INT8 | [✅](models/cv/object_detection/yolox/igie) | [✅](models/cv/object_detection/yolox/ixrt) | 4.2.0 | diff --git a/models/cv/object_detection/yolov12/igie/README.md b/models/cv/object_detection/yolov12/igie/README.md index 537773b9..e65308b6 100644 --- a/models/cv/object_detection/yolov12/igie/README.md +++ b/models/cv/object_detection/yolov12/igie/README.md @@ -56,4 +56,4 @@ bash scripts/infer_yolov12_fp16_performance.sh ## References -YOLOv12: +- [YOLOv12](https://github.com/sunsmarterjie/yolov12) -- Gitee