From 6c85ad6ff51a58697d83d7e9bbc97f683a0eca84 Mon Sep 17 00:00:00 2001
From: "bahawal.baloch" <bahawal.baloch@utopiabrands.com>
Date: Fri, 10 Apr 2026 12:45:44 +0500
Subject: [PATCH] feat: add test script for YOLO inference on surveillance
 video files

---
 test_video.py | 54 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)
 create mode 100644 test_video.py

diff --git a/test_video.py b/test_video.py
new file mode 100644
index 0000000..447d002
--- /dev/null
+++ b/test_video.py
@@ -0,0 +1,54 @@
+import os
+from ultralytics import YOLO
+
+def main():
+    # 1. Paths
+    model_path = "person_detector_best.pt"
+    video_path = os.path.join(
+        "video_data", 
+        "S3 - 55 40 WJ -7", 
+        "download_ch18_20260406080008_20260406090008.mp4"
+    )
+    
+    # 2. Validations
+    if not os.path.exists(model_path):
+        print(f"[!] Error: Model not found at '{model_path}'")
+        return
+
+    if not os.path.exists(video_path):
+        print(f"[!] Error: Video not found at '{video_path}'")
+        return
+
+    # 3. Load Model
+    print(f"[*] Loading model: {model_path}")
+    # Using the Ultralytics YOLO class
+    model = YOLO(model_path)
+
+    # 4. Run Inference
+    print(f"[*] Running inference on video: {video_path}")
+    print("[*] Press 'q' in the video window to stop inference early.")
+    
+    # 'stream=True' is memory-efficient and processes the video frame by frame
+    # 'save=True' will save the annotated video to 'runs/detect/predict'
+    # 'show=True' will display the video as it processes
+    results = model.predict(
+        source=video_path,
+        conf=0.35,       # Confidence threshold (adjust if needed)
+        save=True,       # Save the output video
+        show=True,       # Show video in real-time
+        stream=True,      # Important for large 2GB video files
+        imgsz=1280,
+    )
+
+    # Since stream=True, we must iterate over the results generator to execute inference
+    try:
+        for _ in results:
+            pass
+    except KeyboardInterrupt:
+        print("\n[!] Inference interrupted by user.")
+        
+    print("\n[*] Inference finished.")
+    print("[*] Check the 'runs/detect/predict' directory (or similar) for your annotated video.")
+
+if __name__ == "__main__":
+    main()