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import streamlit as st
##CLIP
scene_labels=['Arrest',
'Arson',
'Explosion',
'public fight',
'Normal',
'Road Accident',
'Robbery',
'Shooting',
'Stealing',
'Vandalism',
'Suspicious activity',
'Tailgating',
'Unauthorized entry',
'Protest/Demonstration',
'Drone suspicious activity',
'Fire/Smoke detection',
'Medical emergency',
'Suspicious package/object',
'Threatening',
'Attack',
'Shoplifting',
'burglary ',
'distress',
'assault']
from transformers import CLIPProcessor, CLIPModel
model_id = "openai/clip-vit-large-patch14"
processor = CLIPProcessor.from_pretrained(model_id)
model = CLIPModel.from_pretrained(model_id)
# Title
st.title("Image Caption Surveillance")
# Input field for URL
image_url = st.text_input("Enter the URL of the image:")
# Display image if a valid URL is provided
if image_url:
try:
st.image(image_url, caption="Uploaded Image")
image = Image.open(requests.get(image_url, stream=True).raw)
inputs = processor(text=scene_labels, images=image, return_tensors="pt", padding=True)
outputs = model(**inputs)
logits_per_image = outputs.logits_per_image # this is the image-text similarity score
probs = logits_per_image.softmax(dim=1) # we can take the softmax to get the label probabilities
context= scene_labels[probs.argmax(-1)]
st.write("context: ", context)
except Exception as e:
st.error(f"Error: {e}")
else:
st.warning("Please enter a valid image URL.")
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