Object Detection
ultralytics
ONNX
yolo
yolo26
pcb
electronic-components
automated-optical-inspection
aoi
jetson
Eval Results (legacy)
Instructions to use Moszer777/pcb-aoi-yolo-rmutt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Moszer777/pcb-aoi-yolo-rmutt with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("Moszer777/pcb-aoi-yolo-rmutt", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- custom_weights_muhd9uvv
- m_new_final_l
- m_new_final_l_1280
- m_new_final_l_1280_b4
- m_new_final_x_1280_b4
- merged-v1-grouped-yolo_l
- merged_T5_run
- merged_T6_run
- merged_T7_ft_run
- new_dataset_final.v2i.yolo26_l
- new_dataset_final2
- new_dataset_final_v2i_yolo26_split_v1_aug_v2_m
- new_dataset_final_v2i_yolo26_split_v1_m
- new_dataset_final_v2i_yolo26_split_v1_s
- new_dataset_final_v2i_yolo26_split_v1_x
- new_dataset_v3_split_v1_l
- new_dataset_v4_aug_v2_l_no-diode
- new_dataset_v5_aug_v2_l_b4
- new_dataset_v6_split_v1_aug_v2_m
- new_dataset_v7_split_v1_aug_v2_m
- newdataset_fix_l_640_b16
- t6_fpic_n
- t6_grouped_l
- t6_l_mlx
- t6_rgb_n
- t6_yolo26l_run
- test_l_1280
- testm_640
- 34.3 kB
- 7.87 kB