File size: 2,133 Bytes
15b8951 | 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 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | import numpy as np
from vlm.webconsole.common.vlm_engine import (
parse_boxes,
draw_boxes,
encode_frame_jpeg,
build_messages,
)
def test_parse_boxes_single():
# ymin=100, xmin=200, ymax=300, xmax=400 trên thang 1000
text = "The phone is at [100, 200, 300, 400]."
boxes = parse_boxes(text, width=1000, height=1000)
assert boxes == [(200, 100, 400, 300)] # (x1, y1, x2, y2)
def test_parse_boxes_scales_to_image():
text = "[0, 0, 500, 1000]"
boxes = parse_boxes(text, width=640, height=480)
# x1=0, y1=0, x2 = 1000/1000*640 = 640, y2 = 500/1000*480 = 240
assert boxes == [(0, 0, 640, 240)]
def test_parse_boxes_none():
assert parse_boxes("no objects detected", 640, 480) == []
def test_parse_boxes_clamps_overflow():
text = "[0, 0, 1200, 1200]" # vượt 1000
boxes = parse_boxes(text, width=100, height=100)
assert boxes == [(0, 0, 100, 100)]
def test_draw_boxes_returns_same_shape_and_copy():
frame = np.zeros((480, 640, 3), dtype=np.uint8)
out = draw_boxes(frame, [(10, 10, 100, 100)], "phone")
assert out.shape == frame.shape
assert out is not frame # không sửa frame gốc
assert out.sum() > 0 # đã vẽ gì đó
def test_encode_frame_jpeg_magic_bytes():
frame = np.zeros((48, 64, 3), dtype=np.uint8)
data = encode_frame_jpeg(frame)
assert isinstance(data, bytes)
assert data[:2] == b"\xff\xd8" # JPEG SOI marker
def test_build_messages_shape():
msgs = build_messages("PIL_PLACEHOLDER", "find the phone")
assert msgs[0]["role"] == "user"
content = msgs[0]["content"]
assert content[0]["type"] == "image"
assert content[0]["image"] == "PIL_PLACEHOLDER"
assert content[1] == {"type": "text", "text": "find the phone"}
import pytest
from vlm.webconsole.common.vlm_engine import VLMEngine
def test_engine_starts_unloaded():
eng = VLMEngine()
assert eng.loaded is False
def test_stream_infer_requires_load():
eng = VLMEngine()
frame = np.zeros((48, 64, 3), dtype=np.uint8)
with pytest.raises(RuntimeError):
list(eng.stream_infer(frame, "describe"))
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