# SPDX-FileCopyrightText: © 2026 Tenstorrent AI ULC
# SPDX-License-Identifier: Apache-2.0
"""README quickstart on the repo's demo input. Writes quickstart_out.png and quickstart_out.json.

  pip install -e code/            # once, in the tt-metal Python environment
  python examples/quickstart.py [image] [query]

The default image is found relative to this file (media/demo_input.png in the repo), so you can
start the script from any directory. A relative [image] path is relative to the current directory.
The outputs go to the current directory.
"""
import json
import os
import sys

from locate_anything import LocateAnything

here = os.path.dirname(os.path.abspath(__file__))
image = sys.argv[1] if len(sys.argv) > 1 else os.path.join(here, "..", "media", "demo_input.png")
query = sys.argv[2] if len(sys.argv) > 2 else "car"

# --- the README snippet ---------------------------------------------------------------
with LocateAnything.from_pretrained(device_id=0) as model:   # downloads weights, opens the chip, warms up
    # the warm-up (warmup_variants="default") makes this first call as fast as later calls
    result = model(image, query)                              # path, PIL image, numpy or torch array
    for label, box in zip(result.labels, result.boxes):
        print(label, box.round(1))                            # x1 y1 x2 y2 in image pixels
    result.draw().save("quickstart_out.png")
# ---------------------------------------------------------------------------------------

with open("quickstart_out.json", "w") as f:
    json.dump(result.to_dict(), f, indent=1)
print(f"raw_text={result.raw_text!r}  model time {result.timing_ms['total']} ms")
print("wrote quickstart_out.png, quickstart_out.json")