Update task_template.py

task_template.py

@@ -0,0 +1,106 @@
+import os
+import sys
+import zipfile
+from pathlib import Path
+
+import numpy as np
+import requests
+from PIL import Image
+
+# CONFIG
+ZIP_FILE = "Dataset.zip"  # Path to the downloaded dataset zip
+DATASET_DIR = Path("Dataset")  # Unzipped folder
+TEMP_OUT_DIR = Path("submission_temp")  # Temporary folder for forged images
+FILE_PATH = "submission.zip"  # Final file to upload
+
+# Leaderboard submission
+BASE_URL  = "http://35.192.205.84:80"
+API_KEY  = "YOUR_API_KEY_HERE"  # REPLACE WITH YOUR API KEY
+TASK_ID   = "22-forging-task"
+
+# 1. UNZIP DATASET
+if not DATASET_DIR.exists():
+    if not os.path.exists(ZIP_FILE):
+        raise FileNotFoundError(f"Could not find {ZIP_FILE}. Please download the dataset first.")
+
+    print(f"Unzipping {ZIP_FILE}...")
+    with zipfile.ZipFile(ZIP_FILE, "r") as zip_ref:
+        zip_ref.extractall(".")
+else:
+    print("Dataset already extracted.")
+
+# Ensure output directory exists
+TEMP_OUT_DIR.mkdir(exist_ok=True)
+
+
+# 2. NAIVE FORGERY ATTACK (IMAGE AVERAGING)
+print("Building forgery submission...")
+
+# Map the Dataset structure: (Source_Folder, Size_Subfolder, Target_Folder)
+CATEGORIES = [
+    ("WM_1", 1, 25),
+    ("WM_2", 26, 50),
+    ("WM_3", 51, 75),
+    ("WM_4", 76, 100),
+    ("WM_5", 101, 125),
+    ("WM_6", 126, 150),
+    ("WM_7", 151, 175),
+    ("WM_8", 176, 200),
+]
+
+
+total_processed = 0
+
+for source_wm, target_start, target_stop in CATEGORIES:
+    print(f"Processing {source_wm} dataset -> Forging onto images {target_start}.png to {target_stop}.png ...")
+
+    source_dir = DATASET_DIR / "watermarked_sources" / source_wm
+    source_images = list(source_dir.glob("*.png"))
+
+    if not source_images:
+        print(f"  [Warning] No source images found in {source_dir}")
+        continue
+
+    target_dir = DATASET_DIR / "clean_targets"
+    target_images = []
+
+    for number in range(target_start, target_stop + 1, 1):
+        temp = target_dir / f"{number}.png"
+        target_images.append(temp)
+
+    for target_path, source_path in zip(target_images, source_images):
+        # Load target clean image
+        target_pil = Image.open(target_path).convert("RGB")
+
+        # Load target source image
+        source_pil = Image.open(source_path).convert("RGB")
+
+        # Convert to numpy arrays for the math
+        target_arr = np.array(target_pil).astype(np.float32)
+        source_arr = np.array(source_pil).astype(np.float32)
+
+        # Blend the Image with a Watermarked Image (Alpha Blending)
+        forged_img = (target_arr * 0.5) + (source_arr * 0.5)
+
+        # Clip values to valid pixel range [0, 255] and convert to uint8
+        forged_img = np.clip(forged_img, 0, 255).astype(np.uint8)
+
+        # Save to our temporary flat directory using the exact original filename (e.g., "104.png")
+        out_path = TEMP_OUT_DIR / target_path.name
+        Image.fromarray(forged_img).save(out_path)
+        total_processed += 1
+
+print(f"\nSuccessfully forged {total_processed} images.")
+if total_processed != 200:
+    print(f"[WARNING] Expected 200 images, but processed {total_processed}. Your submission may be rejected!")
+
+
+# 3. PACKAGE INTO FLAT ZIP FILE
+print(f"Packaging images into {FILE_PATH}...")
+with zipfile.ZipFile(FILE_PATH, "w", zipfile.ZIP_DEFLATED) as zipf:
+    for img_path in TEMP_OUT_DIR.glob("*.png"):
+        zipf.write(img_path, arcname=img_path.name)
+
+print(f"Saved submission file to {FILE_PATH}")
+
+