Xiuren Photo !!top!! -

def __len__(self) -> int: return len(self.paths)

One of the distinctive features of Xiuren Photo is their ability to blend traditional Chinese art forms, such as calligraphy and ink painting, with modern photography. This fusion of old and new creates a unique visual language that is both timeless and contemporary. The collective's use of abstract forms and abstract shapes adds an extra layer of depth and meaning to their images, making them both aesthetically pleasing and intellectually stimulating. xiuren photo

# ---------------------------------------------------------------------- # 3️⃣ Main driver # ---------------------------------------------------------------------- def parse_args(): parser = argparse.ArgumentParser(description="Deep feature extraction for Xiuren photos") parser.add_argument("--data_dir", required=True, help="Folder containing the images") parser.add_argument("--out_path", required=True, help="Where to store .npz (features & filenames)") parser.add_argument("--batch_size", type=int, default=64, help="Batch size for GPU/CPU inference") parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="Device to run on (cuda, cuda:0, cpu, mps, …)") parser.add_argument("--normalize", action="store_true", help="L2‑normalize each feature vector (recommended for similarity search)") return parser.parse_args() def __len__(self) -> int: return len(self

project/ │ ├─ data/ │ └─ xiuren/ │ ├─ img001.jpg │ ├─ img002.png │ └─ ... (any image format Pillow can read) │ ├─ extract_features.py # ← the script we will write └─ requirements.txt # (optional) pip freeze > requirements.txt default="cuda" if torch.cuda.is_available() else "cpu"