Hugging Face's logo

STMicroelectronics
/
st_ssd_mobilenet_v1

Object Detection
Model card Files Community
FBAGSTM commited on
Commit
64f3c1f
•
1 Parent(s): 8161e20

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +25 -25
README.md CHANGED
@@ -68,23 +68,23 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
68
  ### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
69
  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
70
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
71
- |[ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 694.64 | 0.0 | 827.16 | 10.0.0 | 2.0.0 |
72
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 1002.64 | 0.0 | 826.91 | 10.0.0 | 2.0.0 |
73
 
74
 
75
  ### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
76
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
77
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
78
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 9.63 | 103.84 | 10.0.0 | 2.0.0 |
79
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 10.37 | 96.43 | 10.0.0 | 2.0.0 |
80
 
81
 
82
  ### Reference MCU memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
83
  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
84
  |-------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
85
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | STM32H7 | 266.3 | 29.93 | 483.16 | 95.39 | 296.23 | 578.55 | 10.0.0 | |
86
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 379.6 | 34.34 | 675.64 | 106.01 | 413.94 | 781.65 | 10.0.0 | |
87
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | STM32H7 | 456.1 KiB | 33.75 | 675.64 | 105.26| 489.85 | 780.9 | 10.0.0 |
88
 
89
 
90
  ### Reference **MCU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
@@ -92,24 +92,24 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
92
 
93
  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
94
  |-------------------|--------|------------|------------------|------------------|-------------|---------------------|-----------------------|
95
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 149.18 ms | 10.0.0 |
96
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 218.99 ms | 10.0.0 |
97
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 267.18 ms | 10.0.0 |
98
 
99
 
100
  ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
101
 
102
  | Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
103
  |----------------------------------------------------------------------------------------------------------------------------------------------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
104
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 12.34 ms | 15.35 | 84.65 |0 | v5.1.0 | OpenVX |
105
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 18.65 ms | 14.02 | 85.98 |0 | v5.1.0 | OpenVX |
106
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 14.33 ms | 14.12 | 85.88 |0 | v5.1.0 | OpenVX |
107
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 67.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
108
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 100.20 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
109
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 119.00 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
110
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 95.36 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
111
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 139.00 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
112
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 168.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
113
 
114
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
115
 
@@ -120,12 +120,12 @@ Dataset details: [link](https://cocodataset.org/#download) , License [CC BY 4.0]
120
 
121
  | Model | Format | Resolution | AP* |
122
  |-------|--------|------------|----------------|
123
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | 35.80 % |
124
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192.h5) | Float | 192x192x3 | 35.80 % |
125
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | 46.10 % |
126
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224.h5) | Float | 224x224x3 | 46.90 % |
127
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | 50.50 % |
128
- | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256.h5) | Float | 256x256x3 | 51 % |
129
 
130
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001
131
 
 
68
  ### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
69
  |Model | Dataset | Format | Resolution | Series | Internal RAM | External RAM | Weights Flash | STM32Cube.AI version | STEdgeAI Core version |
70
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
71
+ |[ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 694.64 | 0.0 | 827.16 | 10.0.0 | 2.0.0 |
72
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6 | 1002.64 | 0.0 | 826.91 | 10.0.0 | 2.0.0 |
73
 
74
 
75
  ### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
76
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
77
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
78
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 9.63 | 103.84 | 10.0.0 | 2.0.0 |
79
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | COCO-Person | Int8 | 256x256x3 | STM32N6570-DK | NPU/MCU | 10.37 | 96.43 | 10.0.0 | 2.0.0 |
80
 
81
 
82
  ### Reference MCU memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
83
  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
84
  |-------------------|--------|------------|---------|----------------|-------------|---------------|------------|-------------|-------------|-----------------------|
85
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | STM32H7 | 266.3 | 29.93 | 483.16 | 95.39 | 296.23 | 578.55 | 10.0.0 | |
86
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 379.6 | 34.34 | 675.64 | 106.01 | 413.94 | 781.65 | 10.0.0 | |
87
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | STM32H7 | 456.1 KiB | 33.75 | 675.64 | 105.26| 489.85 | 780.9 | 10.0.0 |
88
 
89
 
90
  ### Reference **MCU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
 
92
 
93
  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
94
  |-------------------|--------|------------|------------------|------------------|-------------|---------------------|-----------------------|
95
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 149.18 ms | 10.0.0 |
96
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 218.99 ms | 10.0.0 |
97
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 267.18 ms | 10.0.0 |
98
 
99
 
100
  ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
101
 
102
  | Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
103
  |----------------------------------------------------------------------------------------------------------------------------------------------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
104
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 12.34 ms | 15.35 | 84.65 |0 | v5.1.0 | OpenVX |
105
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 18.65 ms | 14.02 | 85.98 |0 | v5.1.0 | OpenVX |
106
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 14.33 ms | 14.12 | 85.88 |0 | v5.1.0 | OpenVX |
107
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 67.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
108
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 100.20 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
109
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 119.00 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
110
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 95.36 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
111
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 139.00 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
112
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 168.80 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
113
 
114
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
115
 
 
120
 
121
  | Model | Format | Resolution | AP* |
122
  |-------|--------|------------|----------------|
123
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192_int8.tflite) | Int8 | 192x192x3 | 35.80 % |
124
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_192/st_ssd_mobilenet_v1_025_192.h5) | Float | 192x192x3 | 35.80 % |
125
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224_int8.tflite) | Int8 | 224x224x3 | 46.10 % |
126
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_224/st_ssd_mobilenet_v1_025_224.h5) | Float | 224x224x3 | 46.90 % |
127
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256_int8.tflite) | Int8 | 256x256x3 | 50.50 % |
128
+ | [ST SSD Mobilenet v1 0.25](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/st_ssd_mobilenet_v1/ST_pretrainedmodel_public_dataset/coco_2017_person/st_ssd_mobilenet_v1_025_256/st_ssd_mobilenet_v1_025_256.h5) | Float | 256x256x3 | 51 % |
129
 
130
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001
131