Instructions to use rozzman/mobileNetV3FromTimm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use rozzman/mobileNetV3FromTimm with timm:
import timm model = timm.create_model("hf_hub:rozzman/mobileNetV3FromTimm", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -16,3 +16,10 @@ This model is able to recognize 11 high commercially valuable types of wood from
|
|
| 16 |
|
| 17 |
The dataset is from https://www.facom.ufu.br/~backes/wood_dataset.php
|
| 18 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
|
| 17 |
The dataset is from https://www.facom.ufu.br/~backes/wood_dataset.php
|
| 18 |
|
| 19 |
+
The names of these 11 types of wood are shown in the table below
|
| 20 |
+
|
| 21 |
+

|
| 22 |
+
|
| 23 |
+
The cross-sections of these 11 types of wood are shown in the following image
|
| 24 |
+
|
| 25 |
+

|