Instructions to use ipd805/digit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ipd805/digit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ipd805/digit")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ipd805/digit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- config.json +33 -3
config.json
CHANGED
|
@@ -4,8 +4,38 @@
|
|
| 4 |
"spec": {
|
| 5 |
"input_size": [640, 640],
|
| 6 |
"classes": [
|
| 7 |
-
{
|
| 8 |
-
|
| 9 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 10 |
}
|
| 11 |
}
|
|
|
|
| 4 |
"spec": {
|
| 5 |
"input_size": [640, 640],
|
| 6 |
"classes": [
|
| 7 |
+
{
|
| 8 |
+
"id": 0,
|
| 9 |
+
"name": "digit",
|
| 10 |
+
"description": "A numeric character"
|
| 11 |
+
},
|
| 12 |
+
{
|
| 13 |
+
"id": 1,
|
| 14 |
+
"name": "icon",
|
| 15 |
+
"description": "A graphical symbol"
|
| 16 |
+
}
|
| 17 |
+
],
|
| 18 |
+
"preprocessing": {
|
| 19 |
+
"resize": {
|
| 20 |
+
"width": 640,
|
| 21 |
+
"height": 640
|
| 22 |
+
},
|
| 23 |
+
"normalize": {
|
| 24 |
+
"mean": [0.485, 0.456, 0.406],
|
| 25 |
+
"std": [0.229, 0.224, 0.225]
|
| 26 |
+
}
|
| 27 |
+
},
|
| 28 |
+
"postprocessing": {
|
| 29 |
+
"confidence_threshold": 0.5,
|
| 30 |
+
"nms_threshold": 0.4
|
| 31 |
+
}
|
| 32 |
+
},
|
| 33 |
+
"metadata": {
|
| 34 |
+
"description": "YOLOv8 model for detecting digits and icons.",
|
| 35 |
+
"author": "Your Name",
|
| 36 |
+
"date": "2024-07-24",
|
| 37 |
+
"version": "1.0",
|
| 38 |
+
"license": "MIT",
|
| 39 |
+
"tags": ["image-classification", "onnx", "yolov8"]
|
| 40 |
}
|
| 41 |
}
|