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i-robot dbc22a65da | 6 days ago | |
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.. | ||
audio | 2 months ago | |
cv | 6 days ago | |
gnn | 9 months ago | |
lite | 1 year ago | |
nlp | 1 week ago | |
recommend | 5 months ago | |
README.md | 8 months ago | |
README_CN.md | 8 months ago | |
benchmark.md | 10 months ago | |
benchmark_CN.md | 10 months ago |
We've done code refactoring for classic SOTA models,modularized data processing, model definition&creation, training process and other common components with new lanched MindSpore CV/NLP/Audio/Yolo/OCR Series toolbox
Old models were implemented by original MindSpore API with some tricks for training process speedup
More information for model performance, please check benchmark.
model | acc@1 | mindcv recipe | vanilla mindspore |
---|---|---|---|
vgg11 | 71.86 | config | |
vgg13 | 72.87 | config | |
vgg16 | 74.61 | config | link |
vgg19 | 75.21 | config | link |
resnet18 | 70.21 | config | link |
resnet34 | 74.15 | config | link |
resnet50 | 76.69 | config | link |
resnet101 | 78.24 | config | link |
resnet152 | 78.72 | config | link |
resnetv2_50 | 76.90 | config | |
resnetv2_101 | 78.48 | config | |
dpn92 | 79.46 | config | |
dpn98 | 79.94 | config | |
dpn107 | 80.05 | config | |
dpn131 | 80.07 | config | |
densenet121 | 75.64 | config | |
densenet161 | 79.09 | config | |
densenet169 | 77.26 | config | |
densenet201 | 78.14 | config | |
seresnet18 | 71.81 | config | |
seresnet34 | 75.36 | config | |
seresnet50 | 78.31 | config | |
seresnext26 | 77.18 | config | |
seresnext50 | 78.71 | config | |
skresnet18 | 73.09 | config | |
skresnet34 | 76.71 | config | |
skresnet50_32x4d | 79.08 | config | |
resnext50_32x4d | 78.53 | config | |
resnext101_32x4d | 79.83 | config | |
resnext101_64x4d | 80.30 | config | |
resnext152_64x4d | 80.52 | config | |
rexnet_x09 | 77.07 | config | |
rexnet_x10 | 77.38 | config | |
rexnet_x13 | 79.06 | config | |
rexnet_x15 | 79.94 | config | |
rexnet_x20 | 80.64 | config | |
resnest50 | 80.81 | config | |
resnest101 | 82.50 | config | |
res2net50 | 79.35 | config | |
res2net101 | 79.56 | config | |
res2net50_v1b | 80.32 | config | |
res2net101_v1b | 95.41 | config | |
googlenet | 72.68 | config | |
inceptionv3 | 79.11 | config | link |
inceptionv4 | 80.88 | config | link |
mobilenet_v1_025 | 53.87 | config | |
mobilenet_v1_050 | 65.94 | config | |
mobilenet_v1_075 | 70.44 | config | |
mobilenet_v1_100 | 72.95 | config | |
mobilenet_v2_075 | 69.98 | config | |
mobilenet_v2_100 | 72.27 | config | |
mobilenet_v2_140 | 75.56 | config | |
mobilenet_v3_small | 68.10 | config | |
mobilenet_v3_large | 75.23 | config | link |
shufflenet_v1_g3_x0_5 | 57.05 | config | |
shufflenet_v1_g3_x1_5 | 67.77 | config | link |
shufflenet_v2_x0_5 | 57.05 | config | |
shufflenet_v2_x1_0 | 67.77 | config | link |
shufflenet_v2_x1_5 | 57.05 | config | |
shufflenet_v2_x2_0 | 67.77 | config | |
xception | 79.01 | config | link |
ghostnet_50 | 66.03 | config | |
ghostnet_100 | 73.78 | config | |
ghostnet_130 | 75.50 | config | |
nasnet_a_4x1056 | 73.65 | config | |
mnasnet_0.5 | 68.07 | config | |
mnasnet_0.75 | 71.81 | config | |
mnasnet_1.0 | 74.28 | config | |
mnasnet_1.4 | 76.01 | config | |
efficientnet_b0 | 76.89 | config | link |
efficientnet_b1 | 78.95 | config | link |
efficientnet_b2 | 79.80 | link | |
efficientnet_b3 | 80.50 | link | |
efficientnet_v2 | 83.77 | link | |
regnet_x_200mf | 68.74 | config | |
regnet_x_400mf | 73.16 | config | |
regnet_x_600mf | 73.34 | config | |
regnet_x_800mf | 76.04 | config | |
regnet_y_200mf | 70.30 | config | |
regnet_y_400mf | 73.91 | config | |
regnet_y_600mf | 75.69 | config | |
regnet_y_800mf | 76.52 | config | |
mixnet_s | 75.52 | config | |
mixnet_m | 76.64 | config | |
mixnet_l | 78.73 | config | |
hrnet_w32 | 80.64 | config | |
hrnet_w48 | 81.19 | config | |
bit_resnet50 | 76.81 | config | |
bit_resnet50x3 | 80.63 | config | |
bit_resnet101 | 77.93 | config | |
repvgg_a0 | 72.19 | config | |
repvgg_a1 | 74.19 | config | |
repvgg_a2 | 76.63 | config | |
repvgg_b0 | 74.99 | config | |
repvgg_b1 | 78.81 | config | |
repvgg_b2 | 79.29 | config | |
repvgg_b3 | 80.46 | config | |
repvgg_b1g2 | 78.03 | config | |
repvgg_b1g4 | 77.64 | config | |
repvgg_b2g4 | 78.80 | config | |
repmlp_t224 | 76.71 | config | |
convnext_tiny | 81.91 | config | |
convnext_small | 83.40 | config | |
convnext_base | 83.32 | config | |
vit_b_32_224 | 75.86 | config | link |
vit_l_16_224 | 76.34 | config | |
vit_l_32_224 | 73.71 | config | |
swintransformer_tiny | 80.82 | config | link |
pvt_tiny | 74.81 | config | |
pvt_small | 79.66 | config | |
pvt_medium | 81.82 | config | |
pvt_large | 81.75 | config | |
pvt_v2_b0 | 71.50 | config | |
pvt_v2_b1 | 78.91 | config | |
pvt_v2_b2 | 81.99 | config | |
pvt_v2_b3 | 82.84 | config | |
pvt_v2_b4 | 83.14 | config | |
pit_ti | 72.96 | config | |
pit_xs | 78.41 | config | |
pit_s | 80.56 | config | |
pit_b | 81.87 | config | |
coat_lite_tiny | 77.35 | config | |
coat_lite_mini | 78.51 | config | |
coat_tiny | 79.67 | config | |
convit_tiny | 73.66 | config | |
convit_tiny_plus | 77.00 | config | |
convit_small | 81.63 | config | |
convit_small_plus | 81.80 | config | |
convit_base | 82.10 | config | |
convit_base_plus | 81.96 | config | |
crossvit_9 | 73.56 | config | |
crossvit_15 | 81.08 | config | |
crossvit_18 | 81.93 | config | |
mobilevit_xx_small | 68.90 | config | |
mobilevit_x_small | 74.98 | config | |
mobilevit_small | 78.48 | config | |
visformer_tiny | 78.28 | config | |
visformer_tiny_v2 | 78.82 | config | |
visformer_small | 81.76 | config | |
visformer_small_v2 | 82.17 | config | |
edgenext_xx_small | 71.02 | config | |
edgenext_x_small | 75.14 | config | |
edgenext_small | 79.15 | config | |
edgenext_base | 82.24 | config | |
poolformer_s12 | 77.33 | config | |
xcit_tiny_12_p16 | 77.67 | config |
model | map | mindyolo recipe | vanilla mindspore |
---|---|---|---|
yolov8_n | 37.2 | config | |
yolov8_s | 44.6 | config | |
yolov8_m | 50.5 | config | |
yolov8_l | 52.8 | config | |
yolov8_x | 53.7 | config | |
yolov7_t | 37.5 | config | |
yolov7_l | 50.8 | config | |
yolov7_x | 52.4 | config | |
yolov5_n | 27.3 | config | |
yolov5_s | 37.6 | config | link |
yolov5_m | 44.9 | config | |
yolov5_l | 48.5 | config | |
yolov5_x | 50.5 | config | |
yolov4_csp | 45.4 | config | |
yolov4_csp(silu) | 45.8 | config | link |
yolov3_darknet53 | 45.5 | config | link |
yolox_n | 24.1 | config | |
yolox_t | 33.3 | config | |
yolox_s | 40.7 | config | |
yolox_m | 46.7 | config | |
yolox_l | 49.2 | config | |
yolox_x | 51.6 | config | |
yolox_darknet53 | 47.7 | config |
model | map | mind_series recipe | vanilla mindspore |
---|---|---|---|
ssd_vgg16 | 23.2 | link | |
ssd_mobilenetv1 | 22.0 | link | |
ssd_mobilenetv2 | 29.1 | link | |
ssd_resnet50 | 34.3 | link | |
fastrcnn | 58 | link | |
maskrcnn_mobilenetv1 | coming soon | link | |
maskrcnn_resnet50 | coming soon | link |
model | mind_series recipe | vanilla mindspore |
---|---|---|
ocrnet | link | |
deeplab v3 | link | |
deeplab v3 plus | link | |
unet | link |
model | dataset | fscore | mindocr recipe | vanilla mindspore |
---|---|---|---|---|
dbnet_mobilenetv3 | icdar2015 | 77.28 | config | link |
dbnet_resnet18 | icdar2015 | 83.71 | config | link |
dbnet_resnet50 | icdar2015 | 84.99 | config | link |
dbnet_resnet50 | msra-td500 | 85.03 | config | |
dbnet++_resnet50 | icdar2015 | 86.60 | config | |
psenet_resnet152 | icdar2015 | 82.06 | config | link |
east_resnet50 | icdar2015 | 84.87 | config | link |
svtr_tiny | IC03,13,15,IIT,etc | 89.02 | config | |
crnn_vgg7 | IC03,13,15,IIT,etc | 82.03 | config | link |
crnn_resnet34_vd | IC03,13,15,IIT,etc | 84.45 | config | |
rare_resnet34_vd | IC03,13,15,IIT,etc | 85.19 | config |
model | dataset | acc | mindface recipe | vanilla mindspore |
---|---|---|---|---|
arcface_mobilefacenet-0.45g | MS1MV2 | 98.70 | config | |
arcface_r50 | MS1MV2 | 99.76 | config | |
arcface_r100 | MS1MV2 | 99.38 | config | link |
arcface_vit_t | MS1MV2 | 99.71 | config | |
arcface_vit_s | MS1MV2 | 99.76 | config | |
arcface_vit_b | MS1MV2 | 99.81 | config | |
arcface_vit_l | MS1MV2 | 99.75 | config | |
retinaface_mobilenet_0.25 | WiderFace | 90.77/88.2/74.76 | config | link |
retinaface_r50 | WiderFace | 95.07/93.61/84.84 | config | link |
model | mindformer recipe | vanilla mindspore |
---|---|---|
bert_base | config | link |
t5_small | config | |
gpt2_small | config | |
gpt2_13b | config | |
gpt2_52b | config | |
pangu_alpha | config | |
glm_6b | config | |
glm_6b_lora | config | |
llama_7b | config | |
llama_13b | config | |
llama_65b | config | |
llama_7b_lora | config | |
bloom_560m | config | |
bloom_7.1b | config | |
bloom_65b | config | |
bloom_176b | config |
model | mind_series recipe | vanilla mindspore |
---|---|---|
deepfm | link | |
wide&deep | link |
model | mind_series recipe | vanilla mindspore |
---|---|---|
GCN | link |
model | mind_series recipe | vanilla mindspore |
---|---|---|
deepspeech2 | link | |
ecapa_tdnn | link | |
lpcnet | link | |
melgan | link | |
tacotron2 | link |
Mindspore only provides scripts that downloads and preprocesses public datasets. We do not own these datasets and are not responsible for their quality or maintenance. Please make sure you have permission to use the dataset under the dataset’s license. The models trained on these dataset are for non-commercial research and educational purpose only.
To dataset owners: we will remove or update all public content upon request if you don’t want your dataset included on Mindspore, or wish to update it in any way. Please contact us through a Github/Gitee issue. Your understanding and contribution to this community is greatly appreciated.
MindSpore is Apache 2.0 licensed. Please see the LICENSE file.
Models of MindSpore
Python Shell C++ Unity3D Asset Markdown other
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