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Model: EmpathicRobotics/vla-1.7b-qwen3-v2
Source: Original Platform

tools/encode/encode_seed2.py

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+#!/usr/bin/env python3
+"""
+Seed2 encoder -- turns a real image into `<seed2_N>` tokens (0-8191, no
+offset), the reverse of tools/decode/decode_seed2.py. Reuses that module's
+_load_seed2_tokenizer() (same runtime patches: the transformers import move
++ BertLMHeadModel.cls=None guard) rather than re-deriving them -- the public
+ontocord/seed2 repo's own seed2_tokenizer.py still has both bugs unpatched
+(verified 2026-07-23), so any fresh download needs these regardless of
+whether you're encoding or decoding.
+
+Preprocessing: Seed2Tokenizer.encode_image() does its own internal resize to
+224x224 (CLIP-style Resize+Normalize, see seed2_tokenizer.py's `self.processor`)
+-- pass a PIL image straight through, no manual resize needed first.
+
+Usage:
+    python tools/encode/encode_seed2.py --image photo.jpg
+    # prints 32 raw ids; wrap as <seed2> <seed2_N> ... </seed2> to splice
+    # into a prompt for this model (v2's convention -- no offset needed)
+"""
+import argparse
+import os
+import sys
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "decode"))
+from decode_seed2 import _load_seed2_tokenizer, NUM_IMAGE_TOKENS  # noqa: E402
+
+
+def encode_image(image_path: str) -> list:
+    from PIL import Image
+
+    # _load_seed2_tokenizer() os.chdir()s -- resolve a relative image_path
+    # against the original cwd *before* that happens, same class of bug
+    # already fixed once in decode_seed2.py's own --output handling.
+    image_path = os.path.abspath(image_path)
+
+    Seed2Tokenizer, seed2_dir = _load_seed2_tokenizer()
+    tokenizer = Seed2Tokenizer.from_pretrained(seed2_dir).eval()
+    if hasattr(tokenizer, "cuda") and __import__("torch").cuda.is_available():
+        tokenizer = tokenizer.cuda()
+
+    image = Image.open(image_path).convert("RGB")
+    ids = tokenizer.encode_image(image_pil=image)
+    ids = ids.view(-1).tolist()
+
+    bad = [t for t in ids if not (0 <= t < NUM_IMAGE_TOKENS)]
+    if bad:
+        raise ValueError(f"encode_image produced out-of-range ids: {bad[:5]}... (expected [0, {NUM_IMAGE_TOKENS}))")
+    return ids
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
+    ap.add_argument("--image", required=True, help="Path to a real image file")
+    args = ap.parse_args()
+
+    ids = encode_image(args.image)
+    print(f"{len(ids)} seed2 tokens:")
+    print(",".join(str(i) for i in ids))
+    print()
+    print("As a prompt fragment:")
+    print("<seed2> " + " ".join(f"<seed2_{i}>" for i in ids) + " </seed2>")
+
+
+if __name__ == "__main__":
+    main()