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fastdepth

Depth Estimation
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Release AI-ModelZoo-4.0.0

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  1. README.md +11 -11
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@@ -54,25 +54,25 @@ The models are quantized using tensorflow lite converter.
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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
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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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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_224/fast_depth_224_int8_pc.tflite) | NYU depth v2 | Int8 | 224x224x3 | STM32N6 | 2365.98 | 0.0 | 1505.19 | 10.2.0 | 2.2.0 |
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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_224/fast_depth_224_int8_pc.tflite) | NYU depth v2 | Int8 | 256x256x3 | STM32N6 | 2688 | 1024.0 | 1505.19 | 10.2.0 | 2.2.0 |
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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_320/fast_depth_320_int8_pc.tflite) | NYU depth v2 | Int8 | 224x224x3 | STM32N6 | 2800 | 1600 | 1505.17 | 10.2.0 | 2.2.0 |
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  ### Reference **NPU** inference time
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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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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_224/fast_depth_224_int8_pc.tflite) | NYU depth v2 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 24.43 | 40.93 | 10.2.0 | 2.2.0 |
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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_224/fast_depth_224_int8_pc.tflite) | NYU depth v2 | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 55.51 | 18.01 | 10.2.0 | 2.2.0 |
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- | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/pose_estimation/fast_depth/Public_pretrainedmodel_public_dataset/nyu_depth_v2/fast_depth_320/fast_depth_320_int8_pc.tflite) | NYU depth v2 | Int8 | 320x320x3 | STM32N6570-DK | NPU/MCU | 56.07 | 17.83 | 10.2.0 | 2.2.0 |
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  ## Metrics
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+ Measures are done with default STEdgeAI Core version configuration with enabled input / output allocated option.
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  ### Reference **NPU** memory footprint
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+ | Model | Dataset | Format | Resolution | Series | Internal RAM (KiB) | External RAM (KiB) | Weights Flash (KiB) | STEdgeAI Core version |
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+ |------------|---------------|----------|------------|-----------|--------------|--------------|---------------|-----------------------|
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_224/fastdepth_224_int8.tflite) | NYU depth v2 | Int8 | 224x224x3 | STM32N6 | 2728.5 | 0 | 1347.97 | 3.0.0 |
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_256/fastdepth_256_int8.tflite) | NYU depth v2 | Int8 | 256x256x3 | STM32N6 | 2688 | 1024 | 1354.09 | 3.0.0 |
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_320/fastdepth_320_int8.tflite) | NYU depth v2 | Int8 | 320x320x3 | STM32N6 | 2800 | 2800 | 1376.78 | 3.0.0 |
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  ### Reference **NPU** inference time
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+ | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STEdgeAI Core version |
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+ |------------|---------------|----------|------------|------------------|------------------|---------------------|-------------|-------------------------|
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_224/fastdepth_224_int8.tflite) | NYU depth v2 | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 24.49 | 40.83 | 3.0.0 |
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_256/fastdepth_256_int8.tflite) | NYU depth v2 | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 75.01 | 13.33 | 3.0.0 |
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+ | [Fast Depth](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/depth_estimation/fastdepth/Public_pretrainedmodel_public_dataset/nyu_depthv2/fastdepth_320/fastdepth_320_int8.tflite) | NYU depth v2 | Int8 | 320x320x3 | STM32N6570-DK | NPU/MCU | 477.93 | 2.09 | 3.0.0 |
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