refactor: Reorganized references folder

README.md

@@ -86,18 +86,29 @@ docker build . -t <YOUR_IMAGE_TAG>
 You are free to use any training script, but some are already provided for reference. In order to use them, install the specific requirements and check script options as follows:
 
 ```shell
-pip install -r references/classification/OpenFire/fastai/requirements.txt
-python references/classification/OpenFire/fastai/train.py --help
+pip install -r references/requirements.txt
+python references/classification/train.py --help
 ```
 
-You can then run the script with your own arguments:
+You can then use the script to train tour model on one of our datasets:
+
+### Wildfire
+
+Download Dataset from https://drive.google.com/file/d/1Y5IyBLA5xDMS1rBdVs-hsVNGQF3djaR1/view?usp=sharing
+
+This dataset is protected by a password, please contact us at [email protected]
 
-```shell
-python references/classification/OpenFire/fastai/train.py --lr 3e-3 --epochs 4 --pretrained --deterministic
 ```
+python train.py WildFireLght/ --model rexnet1_0x --lr 1e-3 -b 16 --epochs 20 --opt radam --sched onecycle --device 0
+```
+
+### OpenFire
 
-*Please note that most tasks are provided with two training scripts (and their `requirements.txt`): one using [fastai](https://github.com/fastai/fastai) and the other without it.*
+You can also use out opensource dataset without password
 
+```
+python train.py OpenFire/ --use-openfire --model rexnet1_0x --lr 1e-3 -b 16 --epochs 20 --opt radam --sched onecycle --device 0
+```
 
 
 ## Documentation