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#import os
#import streamlit as st
# Fix permission error for Hugging Face Spaces
#os.environ["STREAMLIT_HOME"] = "./safe_streamlit_home"
#os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
#os.makedirs(os.environ["STREAMLIT_HOME"], exist_ok=True)
# Your other imports...
import os
# ✅ Tell Streamlit NOT to collect usage data or write config files
os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
os.environ["XDG_CONFIG_HOME"] = "/tmp"
import streamlit as st
#hf_token = os.getenv("HF_token") # Match the exact name you set in the Secrets tab
# Example usage with requests
#headers = {
# "Authorization": f"Bearer {hf_token}"
#}
# Example: Access a private file or API on Hugging Face
#import requests
#response = requests.get("https://huggingface.co/api/whoami-v2", headers=headers)
#print(response.json())
import os
token = os.getenv("app") # secure
from huggingface_hub import hf_hub_download
#hf_hub_download(
#repo_id="muskan19/Violence_Detector",
#filename="violence_model.h5",
#use_auth_token=token
#)
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), 'src'))
# Streamlit app will be generated here
import streamlit as st
import cv2
import numpy as np
from preprocess import preprocess_frame
#from predict import run_prediction
from predict import run_prediction, load_trained_model
#from src.preprocess import preprocess_frame
#from src.predict import load_trained_model, predict_violence
import tempfile
st.set_page_config(layout="wide")
st.title("🔍 Violence Detection in Video")
st.markdown("Upload a video and let the model detect violent scenes in real-time.")
uploaded_file = st.file_uploader("Upload a video", type=["mp4", "avi","mpeg","mov","mpg"])
model = load_trained_model()
if uploaded_file is not None:
tfile = tempfile.NamedTemporaryFile(delete=False)
tfile.write(uploaded_file.read())
cap = cv2.VideoCapture(tfile.name)
stframe = st.empty()
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
processed = preprocess_frame(frame)
pred = run_prediction(model, processed)
label = "Violent" if pred <= 0.5 else "Non-Violent"
color = (0, 0, 255) if label == "Violent" else (0, 255, 0)
cv2.putText(frame, f'{label} ({pred:.2f})', (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, color, 2)
stframe.image(frame, channels="BGR")
cap.release()
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