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import streamlit as st | |
from transformers import pipeline | |
import matplotlib.pyplot as plt | |
import requests | |
from PIL import Image | |
obj_model = pipeline("object-detection", model="facebook/detr-resnet-50") | |
def get_img_from_url(url): | |
return Image.open(requests.get(url, stream=True).raw) | |
def main(): | |
st.title("Object Detection") | |
with st.form("text_field"): | |
url = st.text_input("Enter an image URL", "https://images.unsplash.com/photo-1543852786-1cf6624b9987?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=987&q=80") | |
st.write("*We recommend to use Unsplash website for browsing an image,[click here!](https://unsplash.com/)") | |
img = get_img_from_url(url) | |
# clicked==True only when the button is clicked | |
clicked = st.form_submit_button("Submit") | |
if clicked: | |
results = obj_model(img) | |
st.write("**ββββββββββββββββββββββ**") | |
st.write("**Input image:**") | |
st.image(img) | |
st.json(results) | |
if __name__ == "__main__": | |
main() |