Create app.py

app.py

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+import streamlit as st
+import cv2
+import tempfile
+import os
+
+# Load model and labels
+config_model = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt.txt'
+frozen_model = 'frozen_inference_graph.pb'
+model = cv2.dnn_DetectionModel(frozen_model, config_model)
+
+class_labels = []
+file_name = 'labels.txt'
+with open(file_name, 'rt') as fpt:
+    class_labels = fpt.read().rstrip('\n').split('\n')
+
+model.setInputSize(320, 320)
+model.setInputScale(1.0 / 127.5)
+model.setInputMean((127.5, 127, 5, 127.5))
+model.setInputSwapRB(True)
+
+# Streamlit UI
+st.title("Object Detection in Videos")
+
+uploaded_file = st.file_uploader("Choose a video...", type=["mp4", "avi", "mov"])
+if uploaded_file is not None:
+    tfile = tempfile.NamedTemporaryFile(delete=False)
+    tfile.write(uploaded_file.read())
+    cap = cv2.VideoCapture(tfile.name)
+
+    # Check if video opened successfully
+    if not cap.isOpened():
+        st.error("Error opening video file")
+
+    # Process video
+    font_scale = 1
+    font = cv2.FONT_HERSHEY_PLAIN
+
+    # Save processed video
+    output_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
+    frame_width = int(cap.get(3))
+    frame_height = int(cap.get(4))
+    out = cv2.VideoWriter(output_file.name, cv2.VideoWriter_fourcc(*'mp4v'), 20, (frame_width, frame_height))
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        ClassIndex, confidence, bbox = model.detect(frame, confThreshold=0.55)
+
+        if len(ClassIndex) != 0:
+            for ClassInd, conf, boxes in zip(ClassIndex.flatten(), confidence.flatten(), bbox):
+                if ClassInd <= 80:
+                    cv2.rectangle(frame, boxes, (255, 0, 0), 2)
+                    cv2.putText(frame, class_labels[ClassInd - 1], (boxes[0] + 10, boxes[1] + 40), font, fontScale=font_scale, color=(0, 255, 0), thickness=2)
+
+        out.write(frame)
+
+    cap.release()
+    out.release()
+
+    # Display processed video
+    st.video(output_file.name)
+
+    # Clean up temporary files
+    os.unlink(tfile.name)
+    os.unlink(output_file.name)