File size: 3,370 Bytes
d75b880 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | 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}")
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