Instructions to use thangkt/PCB-Prune-YOLO-P10-DepGraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use thangkt/PCB-Prune-YOLO-P10-DepGraph with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("thangkt/PCB-Prune-YOLO-P10-DepGraph") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 705 Bytes
f9077ea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"parameters": 2415613,
"counted_parameters": 2415613,
"macs": 3232802400,
"gmacs": 3.2328024,
"flops_estimate": 6465604800,
"gflops_estimate": 6.4656048,
"mean_latency_ms": 9.718659240006673,
"median_latency_ms": 9.886948000712437,
"p95_latency_ms": 10.987326000758912,
"fps": 102.89485157412653,
"model": "outputs/finetune_sparse_reg5e4/p10/weights/best.pt",
"model_size_mb": 4.850336074829102,
"batch_size": 1,
"imgsz": 640,
"device": "cuda:0",
"gpu_name": "Tesla T4",
"gpu_total_memory_mb": 14911.6875,
"peak_gpu_memory_mb": 40.015625,
"python_version": "3.12.12",
"torch_version": "2.10.0+cu128",
"cuda_version": "12.8",
"ultralytics_version": "8.4.115"
} |