diff --git a/draw_eval_results.py b/draw_eval_results.py
new file mode 100644
index 00000000..de51f3dd
--- /dev/null
+++ b/draw_eval_results.py
@@ -0,0 +1,35 @@
+import sys
+import cv2
+import pandas as pd
+import os
+
+eval_result_file = sys.argv[1]
+image_dir = sys.argv[2]
+output_dir = sys.argv[3]
+threshold = float(sys.argv[4])
+
+if not os.path.exists(output_dir):
+    os.mkdir(output_dir)
+
+r = pd.read_csv(eval_result_file, delimiter=" ", names=["ImageID", "Prob", "x1", "y1", "x2", "y2"])
+r['x1'] = r['x1'].astype(int)
+r['y1'] = r['y1'].astype(int)
+r['x2'] = r['x2'].astype(int)
+r['y2'] = r['y2'].astype(int)
+
+
+for image_id, g in r.groupby('ImageID'):
+    image = cv2.imread(os.path.join(image_dir, image_id + ".jpg"))
+    for row in g.itertuples():
+        if row.Prob < threshold:
+            continue
+        cv2.rectangle(image, (row.x1, row.y1), (row.x2, row.y2), (255, 255, 0), 4)
+        label = f"{row.Prob:.2f}"
+        cv2.putText(image, label,
+                    (row.x1 + 20, row.y1 + 40),
+                    cv2.FONT_HERSHEY_SIMPLEX,
+                    1,  # font scale
+                    (255, 0, 255),
+                    2)  # line type
+    cv2.imwrite(os.path.join(output_dir, image_id + ".jpg"), image)
+print(f"Task Done. Processed {r.shape[0]} bounding boxes.")
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