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This catalog contains multiple end-to-end samples for users' reference. The directory structure and specific instructions are as follows.
| sample | description |
|---|---|
| GoogleNet_e2e | Full-process development of GoogleNet image classification application (MindSpore training + AscendCL reasoning) |
| LeNet_e2e | LeNet image classification application full process development (MindSpore training + AscendCL reasoning) |
| ResNet50_e2e | ResNet50 image classification application full process development (MindSpore training + AscendCL reasoning) |
| YOLOV3_mask_detection_e2e | ModelArts+Ascend310 From modelarts to offline deployment, develop mask recognition AI application (picture input + picture output) |
| garbage_e2e | MindSpore+Ascend310 From MindSpore to offline deployment, develop AI applications for garbage classification (picture input + picture output) |
| vgg16_cat_dog_e2e | ModelArts- jupyter +Ascend310 From ModelArts to offline deployment, develop AI applications for cat and dog recognition (picture input + picture output) |