github-actions[bot]
54e6124925
version: sunnypilot v2026.001.000 (dev) date: 2026-05-07T23:07:19 master commit: c28eb958740187620f2282023b8f1997cf90f583
103 lines
3.3 KiB
Python
103 lines
3.3 KiB
Python
import os
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os.environ['DEV'] = 'CPU'
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import pytest
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import numpy as np
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from openpilot.selfdrive.modeld.compile_warp import get_nv12_info, CAMERA_CONFIGS
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from openpilot.sunnypilot.modeld_v2.warp import Warp, MODEL_W, MODEL_H
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VISION_NAME_PAIRS = [ # needed to account for supercombos input_imgs
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('img', 'big_img'),
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('input_imgs', 'big_input_imgs'),
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]
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class MockVisionBuf:
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def __init__(self, w, h):
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self.width = w
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self.height = h
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_, _, _, yuv_size = get_nv12_info(w, h)
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self.data = np.zeros(yuv_size, dtype=np.uint8)
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@pytest.mark.parametrize("buffer_length", [2, 5])
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def test_warp_initialization(buffer_length):
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warp = Warp(buffer_length)
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assert warp.buffer_length == buffer_length
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assert warp.img_buffer_shape == (buffer_length * 6, MODEL_H // 2, MODEL_W // 2)
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@pytest.mark.parametrize("buffer_length", [2, 5])
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@pytest.mark.parametrize("cam_w, cam_h", CAMERA_CONFIGS)
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@pytest.mark.parametrize("road, wide", VISION_NAME_PAIRS)
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def test_warp_process(buffer_length, cam_w, cam_h, road, wide):
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warp = Warp(buffer_length)
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mock_buf = MockVisionBuf(cam_w, cam_h)
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transform = np.eye(3, dtype=np.float32).flatten()
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bufs = {road: mock_buf, wide: mock_buf}
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transforms = {road: transform, wide: transform}
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out = warp.process(bufs, transforms)
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assert isinstance(out, dict)
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assert road in out and wide in out
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assert out[road].shape == (1, 12, MODEL_H // 2, MODEL_W // 2)
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assert out[wide].shape == (1, 12, MODEL_H // 2, MODEL_W // 2)
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key = (cam_w, cam_h)
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assert key in warp.jit_cache
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out2 = warp.process(bufs, transforms)
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assert out2[road].shape == out[road].shape
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@pytest.mark.parametrize("road, wide", VISION_NAME_PAIRS)
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def test_warp_buffer_shift(road, wide):
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warp = Warp(2)
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cam_w, cam_h = CAMERA_CONFIGS[1]
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transform = np.eye(3, dtype=np.float32).flatten()
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buf1 = MockVisionBuf(cam_w, cam_h)
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buf1.data[0] = 255
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bufs1 = {road: buf1, wide: buf1}
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transforms = {road: transform, wide: transform}
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out1 = warp.process(bufs1, transforms)
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road1 = out1[road].numpy().copy()
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buf2 = MockVisionBuf(cam_w, cam_h)
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buf2.data[0] = 128
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bufs2 = {road: buf2, wide: buf2}
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out2 = warp.process(bufs2, transforms)
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assert not np.array_equal(road1, out2[road].numpy())
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@pytest.mark.parametrize("buffer_length", [2, 5])
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@pytest.mark.parametrize("road, wide", VISION_NAME_PAIRS)
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def test_warp_buffer_accumulation(buffer_length, road, wide):
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warp = Warp(buffer_length)
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cam_w, cam_h = CAMERA_CONFIGS[0]
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transform = np.eye(3, dtype=np.float32).flatten()
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transforms = {road: transform, wide: transform}
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outputs = []
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for i in range(buffer_length + 1):
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buf = MockVisionBuf(cam_w, cam_h)
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buf.data[:] = i * 10
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out = warp.process({road: buf, wide: buf}, transforms)
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outputs.append(out[road].numpy().copy())
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assert warp.full_buffers['img'].shape == (buffer_length * 6, MODEL_H // 2, MODEL_W // 2)
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for i in range(1, len(outputs)):
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assert not np.array_equal(outputs[i - 1], outputs[i])
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def test_warp_different_cameras_same_instance():
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warp = Warp(2)
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transform = np.eye(3, dtype=np.float32).flatten()
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buf1 = MockVisionBuf(*CAMERA_CONFIGS[0])
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warp.process({'img': buf1, 'big_img': buf1}, {'img': transform, 'big_img': transform})
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assert len(warp.jit_cache) == 1
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buf2 = MockVisionBuf(*CAMERA_CONFIGS[1])
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warp.process({'img': buf2, 'big_img': buf2}, {'img': transform, 'big_img': transform})
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assert len(warp.jit_cache) == 2
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