Instructions to use Raghavan/ic17mlt_Fast_T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raghavan/ic17mlt_Fast_T with Transformers:
# Load model directly from transformers import FastForSceneTextRecognition model = FastForSceneTextRecognition.from_pretrained("Raghavan/ic17mlt_Fast_T", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- preprocessor_config.json +6 -6
preprocessor_config.json
CHANGED
|
@@ -10,15 +10,15 @@
|
|
| 10 |
"do_rescale": true,
|
| 11 |
"do_resize": true,
|
| 12 |
"image_mean": [
|
| 13 |
-
0.
|
| 14 |
-
0.
|
| 15 |
-
0.
|
| 16 |
],
|
| 17 |
"image_processor_type": "FastImageProcessor",
|
| 18 |
"image_std": [
|
| 19 |
-
0.
|
| 20 |
-
0.
|
| 21 |
-
0.
|
| 22 |
],
|
| 23 |
"min_area": 250,
|
| 24 |
"min_score": 0.88,
|
|
|
|
| 10 |
"do_rescale": true,
|
| 11 |
"do_resize": true,
|
| 12 |
"image_mean": [
|
| 13 |
+
0.485,
|
| 14 |
+
0.456,
|
| 15 |
+
0.406
|
| 16 |
],
|
| 17 |
"image_processor_type": "FastImageProcessor",
|
| 18 |
"image_std": [
|
| 19 |
+
0.229,
|
| 20 |
+
0.224,
|
| 21 |
+
0.225
|
| 22 |
],
|
| 23 |
"min_area": 250,
|
| 24 |
"min_score": 0.88,
|