"""CPU tests of the mask export (no GPU, no SAM 3).
"""
import json

import numpy as np
import pytest

from strangebench.masks import export_sam3_masks as E


def test_rle_round_trip_and_box_convention():
    m = np.zeros((40, 60), dtype=np.uint8)
    m[5:15, 10:30] = 255
    rle = E.rle_from_mask(m)
    assert rle["size"] == [40, 60] and isinstance(rle["counts"], str)
    assert E.rle_bbox(rle) == [10.0, 5.0, 20.0, 10.0]
    assert E.rle_bbox(E.rle_from_mask(np.zeros((4, 4), bool))) is None


def test_box_rle_covers_the_box():
    rle = E.box_rle([10, 5, 20, 10], 40, 60)
    assert E.rle_bbox(rle) == pytest.approx([10.0, 5.0, 20.0, 10.0], abs=1.0)


def test_match_raw_ann_picks_same_class_best_box():
    raw = [{"category_name": "dog", "bbox": [0, 0, 10, 10]}, {"category_name": "cat", "bbox": [50, 50, 10, 10]},
           {"category_name": "cat", "bbox": [0, 0, 10, 10]}]
    assert E.match_raw_ann(raw, "cat", [1, 1, 10, 10])["bbox"] == [0, 0, 10, 10]
    assert E.match_raw_ann(raw, "bird", [0, 0, 5, 5]) is None


def _tree(root, tier="tier2_1typical"):
    (root / tier / "images").mkdir(parents=True)
    d = {"images": [{"id": 1, "scene_id": "s1", "file_name": "s1.png", "height": 40, "width": 60}],
         "categories": [{"id": 1, "name": "dog"}, {"id": 2, "name": "cat"}],
         "annotations": [{"id": 7, "image_id": 1, "category_id": 1, "bbox": [10, 5, 20, 10], "area": 200, "iscrowd": 0},
                         {"id": 8, "image_id": 1, "category_id": 2, "bbox": [40, 20, 10, 10], "area": 100, "iscrowd": 1}]}
    (root / tier / "annotations.json").write_text(json.dumps(d))
    return d


def test_attach_writes_new_tree_and_keeps_boxes(tmp_path):
    tree, out = tmp_path / "shipped", tmp_path / "out"
    shipped = _tree(tree)
    m = np.zeros((40, 60), dtype=np.uint8)
    m[5:15, 10:30] = 255
    rle = E.rle_from_mask(m)
    E.write_json_atomic(out / "fragments" / "tier2_1typical" / "s1.json", {"scene_id": "s1", "anns": [
        {"ann_id": 7, "category": "dog", "bbox_shipped": [10, 5, 20, 10], "segmentation": rle,
         "mask_bbox": E.rle_bbox(rle), "box_iou": 1.0}]})
    E.main(["attach", "--out-root", str(out), "--variant", f"balanced={tree}"])
    got = json.load(open(out / "balanced" / "tier2_1typical" / "annotations.json"))
    a7, a8 = got["annotations"]
    assert a7["segmentation_source"] == "sam3" and a7["segmentation"] == rle
    assert a8["segmentation_source"] == "box"
    assert [a["bbox"] for a in got["annotations"]] == [a["bbox"] for a in shipped["annotations"]]
    assert json.load(open(tree / "tier2_1typical" / "annotations.json")) == shipped
    assert (out / "mask_report.csv").exists()


def test_attach_falls_back_to_box_and_refuses_missing(tmp_path):
    tree, out = tmp_path / "shipped", tmp_path / "out"
    _tree(tree)
    with pytest.raises(SystemExit):
        E.main(["attach", "--out-root", str(out), "--variant", f"balanced={tree}"])
    E.write_json_atomic(out / "fragments" / "tier2_1typical" / "s1.json", {"scene_id": "s1", "anns": [
        {"ann_id": 7, "category": "dog", "bbox_shipped": [10, 5, 20, 10], "segmentation": None, "box_iou": 0.0}]})
    E.main(["attach", "--out-root", str(out), "--variant", f"balanced={tree}"])
    got = json.load(open(out / "balanced" / "tier2_1typical" / "annotations.json"))
    assert got["annotations"][0]["segmentation_source"] == "box"