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--- |
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license: other |
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license_name: sla0044 |
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license_link: >- |
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https://github.com/STMicroelectronics/stm32aimodelzoo/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/LICENSE.md |
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pipeline_tag: object-detection |
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--- |
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# ST Yolo X quantized |
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## **Use case** : `Object detection` |
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# Model description |
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ST Yolo X is a real-time object detection model targeted for real-time processing implemented in Tensorflow. |
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This is an optimized ST version of the well known yolo x, quantized in int8 format using tensorflow lite converter. |
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## Network information |
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| Network information | Value | |
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|-------------------------|-----------------| |
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| Framework | TensorFlow Lite | |
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| Quantization | int8 | |
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| Provenance | TO DO | |
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| Paper | TO DO | |
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## Network inputs / outputs |
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For an image resolution of NxM and NC classes |
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| Input Shape | Description | |
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| ----- | ----------- | |
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| (1, W, H, 3) | Single NxM RGB image with UINT8 values between 0 and 255 | |
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| Output Shape | Description | |
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| ----- | ----------- | |
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| TO DO | |
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## Recommended Platforms |
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| Platform | Supported | Recommended | |
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|----------|-----------|-------------| |
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| STM32L0 | [] | [] | |
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| STM32L4 | [] | [] | |
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| STM32U5 | [] | [] | |
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| STM32H7 | [x] | [] | |
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| STM32MP1 | [x] | [] | |
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| STM32MP2 | [x] | [x] | |
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| STM32N6 | [x] | [x] | |
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# Performances |
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## Metrics |
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Measures are done with default STM32Cube.AI configuration with enabled input / output allocated option. |
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### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset) |
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|Model | Dataset | Format | Resolution | Series | Internal RAM (KiB) | External RAM (KiB)| Weights Flash (KiB)| STM32Cube.AI version | STEdgeAI Core version | |
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|----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6 | 324 | 0.0 | 1028.08 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 624 | 0.0 | 1028.08 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 971.62 | 0.0 | 2547.17 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 320x320x3 | STM32N6 | 968.5 | 0.0 | 1028.08 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_416/st_yolo_x_nano_416_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 416x416x3 | STM32N6 | 2640.62 | 0.0 | 1027.89 | 10.0.0 | 2.0.0 | |
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### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset) |
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| Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version | |
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|--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------| |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 192x192x3 | STM32N6570-DK | NPU/MCU | 5.99 | 166.94 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 8.5 | 117.65 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 21.12 | 47.35 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 320x320x3 | STM32N6570-DK | NPU/MCU | 11.59 | 86.29 | 10.0.0 | 2.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_416/st_yolo_x_nano_416_0.33_0.25_int8.tflite) | COCO-Person | Int8 | 416x416x3 | |
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STM32N6570-DK | NPU/MCU | 17.99 | 55.59 | 10.0.0 | 2.0.0 | |
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### Reference **MCU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset) |
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| Model | Format | Resolution | Series | Activation RAM (KiB) | Runtime RAM (KiB)| Weights Flash (KiB)| Code Flash (KiB)| Total RAM | Total Flash | STM32Cube.AI version | |
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|-------------------|--------|--------------|---------|----------------|-------------|---------------|------------|-------------|--------------|-----------------------| |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25_int8.tflite) | Int8 | 192x192x3 | STM32H7 | 162.42 | 64.05 | 891.18 | 166.19 | 226.47 | 1057.37 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25_int8.tflite) | Int8 | 256x256x3 | STM32H7 | 284.92 | 64.05 | 891.18 | 166.21 | 348.97 | 1057.39 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4_int8.tflite) | Int8 | 256x256x3 | STM32H7 | 463.9 | 83.8 | 2435.76 | 228.22| 547.7 |2663.98 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25_int8.tflite) | Int8 | 320x320x3 | STM32H7 | 442.42 | 64.05 | 891.18 | 166.25 | 506.47 | 1057.43 | 10.0.0 | |
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### Reference **MCU** inference time based on COCO Person dataset (see Accuracy for details on dataset) |
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| Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version | |
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|------------------|--------|------------|------------------|------------------|-------------|---------------------|-----------------------| |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25_int8.tflite) | Int8 | 192x192x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 352.4 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25_int8.tflite) | Int8 | 256x256x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 619.92 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4_int8.tflite) | Int8 | 256x256x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 1696.59 | 10.0.0 | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25_int8.tflite) | Int8 | 320x320x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 988.86 | 10.0.0 | |
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### AP on COCO Person dataset |
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Dataset details: [link](https://cocodataset.org/#download) , License [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/legalcode) , Quotation[[1]](#1) , Number of classes: 80, Number of images: 118,287 |
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| Model | Format | Resolution | AP | |
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|-------|--------|------------|----------------| |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25_int8.tflite) | Int8 | 192x192x3 | 45.1 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_192/st_yolo_x_nano_192_0.33_0.25.h5) | Float | 192x192x3 | 45.2 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25_int8.tflite) | Int8 | 256x256x3 | 53.6 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.33_0.25.h5) | Float | 256x256x3 | 53.3 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4_int8.tflite) | Int8 | 256x256x3 | 58.6 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_256/st_yolo_x_nano_256_0.5_0.4.h5) | Float | 256x256x3 | 58.7 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25_int8.tflite) | Int8 | 320x320x3 | 57.1 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_320/st_yolo_x_nano_320_0.33_0.25.h5) | Float | 320x320x3 | 57.1 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_416/st_yolo_x_nano_416_0.33_0.25_int8.tflite) | Int8 | 416x416x3 | 62.2 % | |
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| [st_yolo_x_nano](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_yolo_x/ST_pretrainedmodel_public_dataset/coco_2017_person/st_yolo_x_nano_416/st_yolo_x_nano_416_0.33_0.25.h5) | Float | 416x416x3 | 62.5 % | |
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\* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001 |
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## Retraining and Integration in a simple example: |
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Please refer to the stm32ai-modelzoo-services GitHub [here](https://github.com/STMicroelectronics/stm32ai-modelzoo-services) |
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# References |
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<a id="1">[1]</a> |
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“Microsoft COCO: Common Objects in Context”. [Online]. Available: https://cocodataset.org/#download. |
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@article{DBLP:journals/corr/LinMBHPRDZ14, |
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author = {Tsung{-}Yi Lin and |
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Michael Maire and |
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Serge J. Belongie and |
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Lubomir D. Bourdev and |
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Ross B. Girshick and |
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James Hays and |
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Pietro Perona and |
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Deva Ramanan and |
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Piotr Doll{'{a} }r and |
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C. Lawrence Zitnick}, |
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title = {Microsoft {COCO:} Common Objects in Context}, |
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journal = {CoRR}, |
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volume = {abs/1405.0312}, |
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year = {2014}, |
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url = {http://arxiv.org/abs/1405.0312}, |
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archivePrefix = {arXiv}, |
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eprint = {1405.0312}, |
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timestamp = {Mon, 13 Aug 2018 16:48:13 +0200}, |
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biburl = {https://dblp.org/rec/bib/journals/corr/LinMBHPRDZ14}, |
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bibsource = {dblp computer science bibliography, https://dblp.org} |
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} |
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