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HAILO15L_object_detection.rst

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HAILO15L_object_detection.rst

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Public Models

  • System host: Intel® Core™ i5-9400 CPU @ 2.90GHz
  • Hailo Dataflow Compiler Version v5.3.0
  • Measurement conditions: Measuring from the SoC, room temperature

Object Detection


Link Legend


Key / Icon Description
⭐ Networks used by Hailo-apps.
S Source – Link to the model's open-source repository.
PT Pretrained – Download the pretrained model file (ZIP format).
HEF, NV12, RGBX Compiled Models – Links to models in various formats: - HEF: RGB format - NV12: NV12 format - RGBX: RGBX format
PR Profiler Report – Download the model's performance profiling report.

Coco


Network Name float mAP Hardware mAP FPS (Batch Size=1) FPS (Batch Size=8) Links Input Resolution (HxWxC) Params (M) OPS (G)
damoyolo_tinynasL20_T 42.5 42.0 106 156 640x640x3 11.35 18.02
damoyolo_tinynasL25_S 46.3 45.1 66.0 95.2 640x640x3 16.25 37.64
damoyolo_tinynasL35_M 49.5 47.7 41.6 55.9 640x640x3 33.98 61.64
efficientdet_lite0 27.1 26.4 126 230 320x320x3 3.56 1.94
efficientdet_lite1 32.1 31.6 77.9 123 384x384x3 4.73 4
efficientdet_lite2 35.8 34.7 46.0 69.0 448x448x3 5.93 6.84
nanodet_repvgg 29.1 28.6 206 293 416x416x3 6.74 11.28
nanodet_repvgg_a1_640 33.3 32.9 80.4 100 640x640x3 10.79 42.8
ssd_mobilenet_v1⭐ 23.2 21.9 303 533 300x300x3 6.79 2.5
ssd_mobilenet_v2 23.7 22.7 237 422 300x300x3 4.46 1.52
tiny_yolov3 14.6 14.3 245 363 416x416x3 8.85 5.58
tiny_yolov4 19.2 17.6 279 391 416x416x3 6.05 6.92
yolo26l 52.8 51.3 19.8 26.1 640x640x3 24.8 86.8
yolo26m 51.5 50.0 26.0 33.4 640x640x3 20.4 68.4
yolo26n 39.9 38.6 106 146 640x640x3 2.4 5.5
yolo26s 47.2 45.9 68.3 102 640x640x3 9.5 20.9
yolov10b⭐ 51.5 50.5 28.4 37.0 640x640x3 20.15 92.09
yolov10n⭐ 38.5 36.9 121 169 640x640x3 2.3 6.8
yolov10s⭐ 45.7 44.8 80.5 114 640x640x3 7.2 21.7
yolov10x⭐ 53.0 50.8 14.4 17.4 640x640x3 31.72 160.56
yolov11l⭐ 52.1 51.4 23.2 30.5 640x640x3 25.3 87.17
yolov11m⭐ 50.7 49.5 33.4 41.4 640x640x3 20.1 68.1
yolov11n⭐ 38.8 37.9 145 207 640x640x3 2.6 6.55
yolov11s⭐ 46.1 45.3 86.7 124 640x640x3 9.4 21.6
yolov11x⭐ 53.4 52.5 9.9 11.6 640x640x3 56.9 195.29
yolov3 38.3 38.2 18.4 22.3 608x608x3 68.79 158.10
yolov3_416 37.4 37.4 30.9 43.6 416x416x3 61.92 65.94
yolov3_gluon 37.0 35.0 19.9 23.2 608x608x3 68.79 140.7
yolov3_gluon_416 35.8 33.9 30.9 43.6 416x416x3 61.92 65.94
yolov4_leaky 48.1 46.8 28.0 39.2 512x512x3 64.33 91.04
yolov5m⭐ 42.6 41.3 58.1 74.8 640x640x3 21.78 52.17
yolov5m6_6.1 50.7 49.4 14.7 16.0 1280x1280x3 35.70 200.04
yolov5m_6.1 44.6 43.2 58.0 74.1 640x640x3 21.17 48.96
yolov5m_wo_spp⭐     56.6 72.7 640x640x3 22.67 52.88
yolov5s⭐ 35.2 34.1 118 152 640x640x3 7.46 17.44
yolov5s_bbox_decoding_only 35.2 34.0 118 152 640x640x3 7.46 17.44
yolov5s_c3tr 37.1 35.8 115 161 640x640x3 10.29 17.02
yolov5s_wo_spp   33.8 129 167 640x640x3 7.85 17.74
yolov5xs_wo_spp 33.0 32.1 195 281 512x512x3 7.85 11.36
yolov6n⭐ 34.3 32.4 190 278 640x640x3 4.32 11.12
yolov6n_0.2.1 35.2 33.9 193 284 640x640x3 4.33 11.06
yolov7⭐ 49.8 48.0 26.8 33.4 640x640x3 36.91 104.51
yolov7_tiny 37.0 36.2 135 181 640x640x3 6.22 13.74
yolov7e6 55.3 53.1 4.54 5.08 1280x1280x3 97.20 515.12
yolov7x⭐ 51.7 50.4 14.9 18.9 640x640x3 71.46 189.68
yolov8l⭐ 51.8 51.4 19.2 23.2 640x640x3 43.7 165.3
yolov8m⭐ 49.6 48.8 39.7 50.1 640x640x3 25.9 78.93
yolov8n⭐ 36.9 36.3 199 278 640x640x3 3.2 8.74
yolov8s⭐ 44.4 43.8 95.7 127 640x640x3 11.2 28.6
yolov8s_bbox_decoding_only 44.6 43.9 95.7 127 640x640x3 11.2 28.6
yolov8x⭐ 52.5 51.9 9.17 10.2 640x640x3 68.2 258
yolov9c⭐ 52.0 51.0 22.1 26.2 640x640x3 25.3 102.1
yolox_l_leaky 48.4 46.2 19.7 24.0 640x640x3 54.17 155.3
yolox_s_leaky 38.0 37.0 90.8 117 640x640x3 8.96 26.74
yolox_s_wide_leaky 42.2 40.6 53.0 65.4 640x640x3 20.12 59.46
yolox_tiny 32.5 31.2 225 329 416x416x3 5.05 6.44
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