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import matplotlib.pyplot as plt
import gradio as gr
from transformers import AutoFeatureExtractor, SegformerForSemanticSegmentation
import torch
import numpy as np
extractor = AutoFeatureExtractor.from_pretrained("hshetty/segmentation-model-finetuned-on-semantic-sidewalk-3e-4-e5")
model = SegformerForSemanticSegmentation.from_pretrained("hshetty/segmentation-model-finetuned-on-semantic-sidewalk-3e-4-e5")
def classify(im):
inputs = extractor(images=im, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
classes = logits[0].detach().cpu().numpy().argmax(axis=0)
colors = np.array([[128,0,0], [128,128,0], [0, 0, 128], [128,0,128], [0, 0, 0]])
return colors[classes]
interface = gr.Interface(fn=classify,
inputs="image",
outputs="image",
title="Self Driving Car App- Semantic Segmentation",
description="This is a self driving car app using Semantic Segmentation as part of week 2 end to end vision application project on CoRise by Abubakar Abid!",
examples=["https://datasets-server.huggingface.co/assets/segments/sidewalk-semantic/--/segments--sidewalk-semantic-2/train/3/pixel_values/image.jpg",
"https://datasets-server.huggingface.co/assets/segments/sidewalk-semantic/--/segments--sidewalk-semantic-2/train/5/pixel_values/image.jpg",
"https://datasets-server.huggingface.co/assets/segments/sidewalk-semantic/--/segments--sidewalk-semantic-2/train/20/pixel_values/image.jpg"])
# FILL HERE
interface.launch()
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