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2b156ca | 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 | # ---------------------------------------------------------------------
# Copyright (c) 2026 Qualcomm Technologies, Inc. and/or its subsidiaries.
# SPDX-License-Identifier: BSD-3-Clause
# ---------------------------------------------------------------------
from __future__ import annotations
import numpy as np
from qai_hub_models.utils.asset_loaders import load_image
from .app import DepthProApp
from .demo import INPUT_IMAGE_ADDRESS
from .demo import main as demo_main
from .model import DepthPro
def test_task() -> None:
"""Run torch DepthPro end-to-end on the sample fixture.
Sanity-checks that the pipeline resolves the HF weights, produces a
depth map at the network's native 1536x1536 unpadded to the original
input resolution, and yields a plausible field of view (roughly the
range Apple demos on natural imagery, 30-100 degrees).
"""
model = DepthPro.from_pretrained()
(_, _, height, width) = model.get_input_spec()["image"][0]
app = DepthProApp(model, height, width)
image = load_image(INPUT_IMAGE_ADDRESS)
prediction = app.estimate_depth(image)
assert prediction.depth.ndim == 2
assert prediction.depth.shape == (image.size[1], image.size[0])
assert np.all(np.isfinite(prediction.depth))
assert prediction.depth.min() > 0
assert 10.0 < prediction.field_of_view < 170.0
assert prediction.focal_length_px > 0
assert prediction.heatmap.size == image.size
def test_demo() -> None:
demo_main(is_test=True)
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