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millionhz/segformer-b0-finetuned-flame
segformer-b0-finetuned-flame is a image segmentation model from millionhz. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
The model was trained for a deep learning project titled Forest Fire Detection.
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From the Hugging Face model README
The model was trained for a deep learning project titled Forest Fire Detection.
The model is intended to be used for fire detection through image segmentation.
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.
Here is how to use this model to segment an image:
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)
The license for this model can be found here.