Object Detection
ultralytics
yolo
yolov11
poultry
chicken
egg
broiler
agriculture
smart-farming
animal-welfare
precision-livestock-farming
Eval Results (legacy)
Instructions to use Williamsanderson/PoultryVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Williamsanderson/PoultryVision with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("Williamsanderson/PoultryVision") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Initial release: YOLOv11m fine-tuned on PoultryVision dataset (79.3% mAP50-95, beats paper YOLOv11x by +8.5pts)
eacfff4 verified | task: detect | |
| mode: train | |
| model: runs\detect\results\poultry_vision_v2\weights\last.pt | |
| data: dataset\data.yaml | |
| epochs: 70 | |
| time: null | |
| patience: 85 | |
| batch: 4 | |
| imgsz: 640 | |
| save: true | |
| save_period: 10 | |
| cache: false | |
| device: '0' | |
| workers: 4 | |
| project: results | |
| name: poultry_vision_v2 | |
| exist_ok: true | |
| pretrained: true | |
| optimizer: AdamW | |
| verbose: true | |
| seed: 0 | |
| deterministic: true | |
| single_cls: false | |
| rect: false | |
| cos_lr: false | |
| close_mosaic: 10 | |
| resume: runs\detect\results\poultry_vision_v2\weights\last.pt | |
| amp: true | |
| fraction: 1.0 | |
| profile: false | |
| freeze: null | |
| multi_scale: 0.0 | |
| compile: false | |
| overlap_mask: true | |
| mask_ratio: 4 | |
| dropout: 0.0 | |
| val: true | |
| split: val | |
| save_json: false | |
| conf: null | |
| iou: 0.7 | |
| max_det: 300 | |
| half: false | |
| dnn: false | |
| plots: true | |
| end2end: null | |
| source: null | |
| vid_stride: 1 | |
| stream_buffer: false | |
| visualize: false | |
| augment: false | |
| agnostic_nms: false | |
| classes: null | |
| retina_masks: false | |
| embed: null | |
| show: false | |
| save_frames: false | |
| save_txt: false | |
| save_conf: false | |
| save_crop: false | |
| show_labels: true | |
| show_conf: true | |
| show_boxes: true | |
| line_width: null | |
| format: torchscript | |
| keras: false | |
| optimize: false | |
| int8: false | |
| dynamic: false | |
| simplify: true | |
| opset: null | |
| workspace: null | |
| nms: false | |
| lr0: 0.001 | |
| lrf: 0.01 | |
| momentum: 0.937 | |
| weight_decay: 0.0005 | |
| warmup_epochs: 3 | |
| warmup_momentum: 0.8 | |
| warmup_bias_lr: 0.1 | |
| box: 7.5 | |
| cls: 0.5 | |
| dfl: 1.5 | |
| pose: 12.0 | |
| kobj: 1.0 | |
| rle: 1.0 | |
| angle: 1.0 | |
| nbs: 64 | |
| hsv_h: 0.015 | |
| hsv_s: 0.7 | |
| hsv_v: 0.4 | |
| degrees: 10 | |
| translate: 0.1 | |
| scale: 0.5 | |
| shear: 0.0 | |
| perspective: 0.0 | |
| flipud: 0.0 | |
| fliplr: 0.5 | |
| bgr: 0.0 | |
| mosaic: 1.0 | |
| mixup: 0.1 | |
| cutmix: 0.0 | |
| copy_paste: 0.0 | |
| copy_paste_mode: flip | |
| auto_augment: randaugment | |
| erasing: 0.4 | |
| cfg: null | |
| tracker: botsort.yaml | |
| save_dir: C:\Users\HP\Downloads\Dataset Model Firm\PoultryVision\runs\detect\results\poultry_vision_v2 | |