The provided pretrained model was finetuned on the FLAME dataset for 3 epochs with a learning rate of 1e-3 and was able to score an IOU score of 0.745 on the test examples.

How to use

Here is how to use this model to segment an image:

python

from transformers import SegformerImageProcessor, SegformerForSemanticSegmentation
from PIL import Image
import requests

processor = AutoFeatureExtractor.from_pretrained("millionhz/segformer-b0-finetuned-flame")
model = SegformerForSemanticSegmentation.from_pretrained("millionhz/segformer-b0-finetuned-flame")


url = <add url here>
image = Image.open(requests.get(url, stream=True).raw)

inputs = feature_extractor(images=image, return_tensors="pt")
outputs = model(**inputs)

License

The license for this model can be found here.