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Merged
merged 6 commits into from
Aug 8, 2025
Merged

Add yolo models #228

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c60acf9
add yolo v8 models
cregouby Aug 2, 2025
2470ca1
add yolo v11
cregouby Aug 2, 2025
2773ffd
yolo need ultralytics
cregouby Aug 2, 2025
c767090
special management for yolo models
cregouby Aug 8, 2025
cffd1cc
lighten the install with cpu-only software-stack
cregouby Aug 8, 2025
ca1a553
add another batch of yolo models
cregouby Aug 8, 2025
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3 changes: 2 additions & 1 deletion .github/workflows/models.yaml
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Expand Up @@ -21,6 +21,7 @@ jobs:
python-version: '3.10'
- run: |
python -m pip install --upgrade pip
pip install torch torchvision boto3
pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
pip install boto3 ultralytics
- run: |
python tools/convert-models.py
31 changes: 31 additions & 0 deletions tools/convert-models.py
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Expand Up @@ -3,6 +3,7 @@
import os
import boto3
from botocore.exceptions import ClientError
from ultralytics import settings


def upload_blob(bucket_name, source_file_name, destination_blob_name):
Expand Down Expand Up @@ -110,9 +111,34 @@ def blob_exist(bucket_name, blob_name):
'fasterrcnn_resnet50_v2': 'https://download.pytorch.org/models/fasterrcnn_resnet50_fpn_v2_coco-dd69338a.pth',
'fasterrcnn_mobilenet_v3_large': 'https://download.pytorch.org/models/fasterrcnn_mobilenet_v3_large_fpn-fb6a3cc7.pth',
'fasterrcnn_mobilenet_v3_large_320': 'https://download.pytorch.org/models/fasterrcnn_mobilenet_v3_large_320_fpn-907ea3f9.pth',
'yolo_v8_l': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l.pt',
'yolo_v8_l_seg': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l-seg.pt',
'yolo_v8_m': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8m.pt',
'yolo_v8_m_seg': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8m-seg.pt',
'yolo_v8_n': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt',
'yolo_v8_s': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8s.pt',
'yolo_v8_s_seg': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8s-seg.pt',
'yolo_v8_x': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8x.pt',
'yolo_v11_l': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11l.pt',
'yolo_v11_m': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11m.pt',
'yolo_v11_n': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n.pt',
'yolo_v11_s': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s.pt',
'yolo_v11_s_cls': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s-cls.pt',
'yolo_v11_s_obb': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s-obb.pt',
'yolo_v11_s_pose': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s-pose.pt',
'yolo_v11_s_seg': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s-seg.pt',
'yolo_v11_x': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11x.pt',
'yolo_v12_l': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12l.pt',
'yolo_v12_m': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12m.pt',
'yolo_v12_n': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12n.pt',
'yolo_v12_s': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12s.pt',
'yolo_v12_x': 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12x.pt',
}

os.makedirs("models", exist_ok=True)
# yolo specifics
os.makedirs("runs", exist_ok=True)
settings.update({"runs_dir": "runs/", "weights_dir": "models/", "sync": False})

for name, url in models.items():
fpath = "models/" + name + ".pth"
Expand All @@ -124,6 +150,11 @@ def blob_exist(bucket_name, blob_name):
# download from url, convert and upload the converted weights
m = load_state_dict_from_url(url, progress=False)
converted = {}

# yolo models weights are embedded in a BaseModel per https://github.com/ultralytics/ultralytics/blob/main/ultralytics/nn/tasks.py#L309
if name.startswith("yolo_"):
m = m["model"].model.float().state_dict()

for nm, par in m.items():
converted.update([(nm, par.clone())])
torch.save(converted, fpath, _use_new_zipfile_serialization=True)
Expand Down
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