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@@ -66,26 +66,26 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
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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 |
68
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
69
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 392 | 0.0 | 10804.81 | 10.0.0 | 2.0.0 |
70
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | ST-Person | Int8 | 224x224x3 | STM32N6 | 392 | 0.0 | 10804.81 | 10.0.0 | 2.0.0 |
71
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | COCO-Person | Int8 | 416x416x3 | STM32N6 | 1880.12 | 0.0 | 10829 | 10.0.0 | 2.0.0 |
72
 
73
 
74
  ### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
75
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
76
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
77
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 30.67 | 32.61 |10.0.0 | 2.0.0 |
78
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | ST-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 30.67 | 32.61| 10.0.0 | 2.0.0 |
79
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | COCO-Person | Int8 | 416x416x3 | STM32N6570-DK | NPU/MCU | 50.91 | 19.64 | 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
 
84
  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
85
  |-------------------|--------|--------------|---------|----------------|-------------|---------------|------------|-------------|--------------|-----------------------|
86
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | STM32H7 | 220.6 KiB | 7.98 KiB | 10775.98 KiB | 55.85 KiB | 228.58 KiB | 10831.83 KiB | 10.0.0 |
87
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 249.35 KiB | 7.98 KiB | 10775.98 KiB | 55.8 KiB | 257.33 KiB | 10831.78 KiB | 10.0.0 |
88
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | STM32H7 | 1263.07 KiB | 8.03 KiB | 10775.98 KiB | 55.85 KiB | 1271.1 KiB | 10831.83 KiB | 10.0.0 |
89
 
90
 
91
  ### Reference **MCU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
@@ -93,9 +93,9 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
93
 
94
  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
95
  |------------------|--------|------------|------------------|------------------|-------------|---------------------|-----------------------|
96
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 3006.3 ms | 10.0.0 |
97
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 2742.3 ms | 10.0.0 |
98
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 10468.2 ms | 10.0.0 |
99
 
100
 
101
  ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
@@ -103,12 +103,12 @@ Measures are done with default STM32Cube.AI configuration with enabled input / o
103
 
104
  | Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
105
  |--------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
106
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 120.8 ms | 3.45 | 96.55 |0 | v5.1.0 | OpenVX |
107
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 425.6 ms | 2.74 | 97.26 |0 | v5.1.0 | OpenVX |
108
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 410.50 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
109
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 1347 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
110
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 619.70 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
111
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 2105 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
112
 
113
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
114
 
@@ -118,12 +118,12 @@ Dataset details: [link](https://cocodataset.org/#download) , License [CC BY 4.0]
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119
  | Model | Format | Resolution | AP |
120
  |-------|--------|------------|----------------|
121
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | 33.7 % |
122
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192.h5) | Float | 192x192x3 | 34.5 % |
123
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | 37.3 % |
124
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224.h5) | Float | 224x224x3 | 38.4 % |
125
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | 50.7 % |
126
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416.h5) | Float | 416x416x3 | 51.5 % |
127
 
128
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001
129
 
@@ -131,7 +131,7 @@ Dataset details: [link](https://cocodataset.org/#download) , License [CC BY 4.0]
131
 
132
  | Model | Format | Resolution | AP |
133
  |-------|--------|------------|----------------|
134
- | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | 34.0 % |
135
 
136
 
137
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001
 
66
  ### Reference **NPU** memory footprint based on COCO Person dataset (see Accuracy for details on dataset)
67
  |Model | Dataset | Format | Resolution | Series | Internal RAM (KiB) | External RAM (KiB)| Weights Flash (KiB) | STM32Cube.AI version | STEdgeAI Core version |
68
  |----------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
69
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6 | 392 | 0.0 | 10804.81 | 10.0.0 | 2.0.0 |
70
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | ST-Person | Int8 | 224x224x3 | STM32N6 | 392 | 0.0 | 10804.81 | 10.0.0 | 2.0.0 |
71
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | COCO-Person | Int8 | 416x416x3 | STM32N6 | 1880.12 | 0.0 | 10829 | 10.0.0 | 2.0.0 |
72
 
73
 
74
  ### Reference **NPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
75
  | Model | Dataset | Format | Resolution | Board | Execution Engine | Inference time (ms) | Inf / sec | STM32Cube.AI version | STEdgeAI Core version |
76
  |--------|------------------|--------|-------------|------------------|------------------|---------------------|-------|----------------------|-------------------------|
77
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | COCO-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 30.67 | 32.61 |10.0.0 | 2.0.0 |
78
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | ST-Person | Int8 | 224x224x3 | STM32N6570-DK | NPU/MCU | 30.67 | 32.61| 10.0.0 | 2.0.0 |
79
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | COCO-Person | Int8 | 416x416x3 | STM32N6570-DK | NPU/MCU | 50.91 | 19.64 | 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
 
84
  | Model | Format | Resolution | Series | Activation RAM | Runtime RAM | Weights Flash | Code Flash | Total RAM | Total Flash | STM32Cube.AI version |
85
  |-------------------|--------|--------------|---------|----------------|-------------|---------------|------------|-------------|--------------|-----------------------|
86
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | STM32H7 | 220.6 KiB | 7.98 KiB | 10775.98 KiB | 55.85 KiB | 228.58 KiB | 10831.83 KiB | 10.0.0 |
87
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | STM32H7 | 249.35 KiB | 7.98 KiB | 10775.98 KiB | 55.8 KiB | 257.33 KiB | 10831.78 KiB | 10.0.0 |
88
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | STM32H7 | 1263.07 KiB | 8.03 KiB | 10775.98 KiB | 55.85 KiB | 1271.1 KiB | 10831.83 KiB | 10.0.0 |
89
 
90
 
91
  ### Reference **MCU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
 
93
 
94
  | Model | Format | Resolution | Board | Execution Engine | Frequency | Inference time (ms) | STM32Cube.AI version |
95
  |------------------|--------|------------|------------------|------------------|-------------|---------------------|-----------------------|
96
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 3006.3 ms | 10.0.0 |
97
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 2742.3 ms | 10.0.0 |
98
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | STM32H747I-DISCO | 1 CPU | 400 MHz | 10468.2 ms | 10.0.0 |
99
 
100
 
101
  ### Reference **MPU** inference time based on COCO Person dataset (see Accuracy for details on dataset)
 
103
 
104
  | Model | Format | Resolution | Quantization | Board | Execution Engine | Frequency | Inference time (ms) | %NPU | %GPU | %CPU | X-LINUX-AI version | Framework |
105
  |--------------|--------|------------|---------------|-------------------|------------------|-----------|---------------------|-------|-------|------|--------------------|-----------------------|
106
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 120.8 ms | 3.45 | 96.55 |0 | v5.1.0 | OpenVX |
107
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel** | STM32MP257F-DK2 | NPU/GPU | 800 MHz | 425.6 ms | 2.74 | 97.26 |0 | v5.1.0 | OpenVX |
108
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 410.50 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
109
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel | STM32MP157F-DK2 | 2 CPU | 800 MHz | 1347 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
110
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 619.70 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
111
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | per-channel | STM32MP135F-DK2 | 1 CPU | 1000 MHz | 2105 ms | NA | NA |100 | v5.1.0 | TensorFlowLite 2.11.0 |
112
 
113
  ** **To get the most out of MP25 NPU hardware acceleration, please use per-tensor quantization**
114
 
 
118
 
119
  | Model | Format | Resolution | AP |
120
  |-------|--------|------------|----------------|
121
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192_int8.tflite) | Int8 | 192x192x3 | 33.7 % |
122
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_192/tiny_yolo_v2_192.h5) | Float | 192x192x3 | 34.5 % |
123
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | 37.3 % |
124
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_224/tiny_yolo_v2_224.h5) | Float | 224x224x3 | 38.4 % |
125
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416_int8.tflite) | Int8 | 416x416x3 | 50.7 % |
126
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_public_dataset/coco_2017_person/tiny_yolo_v2_416/tiny_yolo_v2_416.h5) | Float | 416x416x3 | 51.5 % |
127
 
128
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001
129
 
 
131
 
132
  | Model | Format | Resolution | AP |
133
  |-------|--------|------------|----------------|
134
+ | [tiny_yolo_v2](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/object_detection/tiny_yolo_v2/ST_pretrainedmodel_custom_dataset/st_person/tiny_yolo_v2_224/tiny_yolo_v2_224_int8.tflite) | Int8 | 224x224x3 | 34.0 % |
135
 
136
 
137
  \* EVAL_IOU = 0.4, NMS_THRESH = 0.5, SCORE_THRESH =0.001