Instructions to use Antevolt/Sky-OG-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use Antevolt/Sky-OG-Model with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("Antevolt/Sky-OG-Model") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Box offset correction (-20,-8) for CAD projection bias
Browse files
indomain/dashboard_export/review_app.py
CHANGED
|
@@ -39,6 +39,12 @@ INFERNO = np.array(_INFERNO_FLAT, dtype=np.uint8).reshape(256, 3)
|
|
| 39 |
|
| 40 |
LABEL_FIELDS = ["module_id", "decision", "label", "mode", "vmin", "vmax", "reviewed_at"]
|
| 41 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 42 |
# ---------------------------------------------------------------------------
|
| 43 |
|
| 44 |
|
|
@@ -198,8 +204,9 @@ class Store:
|
|
| 198 |
if arr is not None:
|
| 199 |
st = {"p2": round(float(np.percentile(arr, 2)), 2),
|
| 200 |
"p98": round(float(np.percentile(arr, 98)), 2)}
|
|
|
|
| 201 |
return {"has": True, "w": info["w"], "h": info["h"],
|
| 202 |
-
"quad":
|
| 203 |
|
| 204 |
# -- labels ----------------------------------------------------------
|
| 205 |
def save_label(self, rec):
|
|
|
|
| 39 |
|
| 40 |
LABEL_FIELDS = ["module_id", "decision", "label", "mode", "vmin", "vmax", "reviewed_at"]
|
| 41 |
|
| 42 |
+
# Constant correction for the systematic CAD->image projection bias, in native
|
| 43 |
+
# frame pixels (640x512). Box overlay is shifted by (BOX_DX, BOX_DY) so it sits
|
| 44 |
+
# on the individual module. Negative = left / up.
|
| 45 |
+
BOX_DX = -20.0
|
| 46 |
+
BOX_DY = -8.0
|
| 47 |
+
|
| 48 |
# ---------------------------------------------------------------------------
|
| 49 |
|
| 50 |
|
|
|
|
| 204 |
if arr is not None:
|
| 205 |
st = {"p2": round(float(np.percentile(arr, 2)), 2),
|
| 206 |
"p98": round(float(np.percentile(arr, 98)), 2)}
|
| 207 |
+
quad = [[x + BOX_DX, y + BOX_DY] for x, y in info["quad"]]
|
| 208 |
return {"has": True, "w": info["w"], "h": info["h"],
|
| 209 |
+
"quad": quad, **st}
|
| 210 |
|
| 211 |
# -- labels ----------------------------------------------------------
|
| 212 |
def save_label(self, rec):
|