255 lines
8.0 KiB
Python
255 lines
8.0 KiB
Python
import json
|
|
import os
|
|
from typing import Any
|
|
|
|
import pytest
|
|
|
|
import supervision as sv
|
|
from test.test_utils import mock_detections
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
(
|
|
"detections",
|
|
"custom_data",
|
|
"second_detections",
|
|
"second_custom_data",
|
|
"file_name",
|
|
"expected_result",
|
|
),
|
|
[
|
|
(
|
|
mock_detections(
|
|
xyxy=[[10, 20, 30, 40], [50, 60, 70, 80]],
|
|
confidence=[0.7, 0.8],
|
|
class_id=[0, 0],
|
|
tracker_id=[0, 1],
|
|
data={"class_name": ["person", "person"]},
|
|
),
|
|
{"frame_number": 42},
|
|
mock_detections(
|
|
xyxy=[[15, 25, 35, 45], [55, 65, 75, 85]],
|
|
confidence=[0.6, 0.9],
|
|
class_id=[1, 1],
|
|
tracker_id=[2, 3],
|
|
data={"class_name": ["car", "car"]},
|
|
),
|
|
{"frame_number": 43},
|
|
"test_detections.json",
|
|
[
|
|
{
|
|
"x_min": 10,
|
|
"y_min": 20,
|
|
"x_max": 30,
|
|
"y_max": 40,
|
|
"class_id": 0,
|
|
"confidence": 0.699999988079071,
|
|
"tracker_id": 0,
|
|
"class_name": "person",
|
|
"frame_number": 42,
|
|
},
|
|
{
|
|
"x_min": 50,
|
|
"y_min": 60,
|
|
"x_max": 70,
|
|
"y_max": 80,
|
|
"class_id": 0,
|
|
"confidence": 0.800000011920929,
|
|
"tracker_id": 1,
|
|
"class_name": "person",
|
|
"frame_number": 42,
|
|
},
|
|
{
|
|
"x_min": 15,
|
|
"y_min": 25,
|
|
"x_max": 35,
|
|
"y_max": 45,
|
|
"class_id": 1,
|
|
"confidence": 0.6000000238418579,
|
|
"tracker_id": 2,
|
|
"class_name": "car",
|
|
"frame_number": 43,
|
|
},
|
|
{
|
|
"x_min": 55,
|
|
"y_min": 65,
|
|
"x_max": 75,
|
|
"y_max": 85,
|
|
"class_id": 1,
|
|
"confidence": 0.8999999761581421,
|
|
"tracker_id": 3,
|
|
"class_name": "car",
|
|
"frame_number": 43,
|
|
},
|
|
],
|
|
), # Multiple detections
|
|
(
|
|
mock_detections(
|
|
xyxy=[[60, 70, 80, 90], [100, 110, 120, 130]],
|
|
tracker_id=[4, 5],
|
|
data={"class_name": ["bike", "dog"]},
|
|
),
|
|
{"frame_number": 44},
|
|
mock_detections(
|
|
xyxy=[[65, 75, 85, 95], [105, 115, 125, 135]],
|
|
confidence=[0.5, 0.4],
|
|
data={"class_name": ["tree", "cat"]},
|
|
),
|
|
{"frame_number": 45},
|
|
"test_detections_missing_fields.json",
|
|
[
|
|
{
|
|
"x_min": 60,
|
|
"y_min": 70,
|
|
"x_max": 80,
|
|
"y_max": 90,
|
|
"class_id": "",
|
|
"confidence": "",
|
|
"tracker_id": 4,
|
|
"class_name": "bike",
|
|
"frame_number": 44,
|
|
},
|
|
{
|
|
"x_min": 100,
|
|
"y_min": 110,
|
|
"x_max": 120,
|
|
"y_max": 130,
|
|
"class_id": "",
|
|
"confidence": "",
|
|
"tracker_id": 5,
|
|
"class_name": "dog",
|
|
"frame_number": 44,
|
|
},
|
|
{
|
|
"x_min": 65,
|
|
"y_min": 75,
|
|
"x_max": 85,
|
|
"y_max": 95,
|
|
"class_id": "",
|
|
"confidence": 0.5,
|
|
"tracker_id": "",
|
|
"class_name": "tree",
|
|
"frame_number": 45,
|
|
},
|
|
{
|
|
"x_min": 105,
|
|
"y_min": 115,
|
|
"x_max": 125,
|
|
"y_max": 135,
|
|
"class_id": "",
|
|
"confidence": 0.4000000059604645,
|
|
"tracker_id": "",
|
|
"class_name": "cat",
|
|
"frame_number": 45,
|
|
},
|
|
],
|
|
), # Missing fields
|
|
(
|
|
mock_detections(
|
|
xyxy=[[10, 11, 12, 13]],
|
|
confidence=[0.95],
|
|
data={"class_name": "unknown", "is_detected": True, "score": 1},
|
|
),
|
|
{"frame_number": 46},
|
|
mock_detections(
|
|
xyxy=[[14, 15, 16, 17]],
|
|
data={"class_name": "artifact", "is_detected": False, "score": 0.85},
|
|
),
|
|
{"frame_number": 47},
|
|
"test_detections_varied_data.json",
|
|
[
|
|
{
|
|
"x_min": 10,
|
|
"y_min": 11,
|
|
"x_max": 12,
|
|
"y_max": 13,
|
|
"class_id": "",
|
|
"confidence": 0.949999988079071,
|
|
"tracker_id": "",
|
|
"class_name": "unknown",
|
|
"is_detected": "True",
|
|
"score": "1",
|
|
"frame_number": 46,
|
|
},
|
|
{
|
|
"x_min": 14,
|
|
"y_min": 15,
|
|
"x_max": 16,
|
|
"y_max": 17,
|
|
"class_id": "",
|
|
"confidence": "",
|
|
"tracker_id": "",
|
|
"class_name": "artifact",
|
|
"is_detected": "False",
|
|
"score": "0.85",
|
|
"frame_number": 47,
|
|
},
|
|
],
|
|
), # Inconsistent Data Types
|
|
(
|
|
mock_detections(
|
|
xyxy=[[20, 21, 22, 23]],
|
|
),
|
|
{
|
|
"metadata": {"sensor_id": 101, "location": "north"},
|
|
"tags": ["urgent", "review"],
|
|
},
|
|
mock_detections(
|
|
xyxy=[[14, 15, 16, 17]],
|
|
),
|
|
{
|
|
"metadata": {"sensor_id": 104, "location": "west"},
|
|
"tags": ["not-urgent", "done"],
|
|
},
|
|
"test_detections_complex_data.json",
|
|
[
|
|
{
|
|
"x_min": 20,
|
|
"y_min": 21,
|
|
"x_max": 22,
|
|
"y_max": 23,
|
|
"class_id": "",
|
|
"confidence": "",
|
|
"tracker_id": "",
|
|
"metadata": {"sensor_id": 101, "location": "north"},
|
|
"tags": ["urgent", "review"],
|
|
},
|
|
{
|
|
"x_min": 14,
|
|
"y_min": 15,
|
|
"x_max": 16,
|
|
"y_max": 17,
|
|
"class_id": "",
|
|
"confidence": "",
|
|
"tracker_id": "",
|
|
"metadata": {"sensor_id": 104, "location": "west"},
|
|
"tags": ["not-urgent", "done"],
|
|
},
|
|
],
|
|
), # Complex Data
|
|
],
|
|
)
|
|
def test_json_sink(
|
|
detections: mock_detections,
|
|
custom_data: dict[str, Any],
|
|
second_detections: mock_detections,
|
|
second_custom_data: dict[str, Any],
|
|
file_name: str,
|
|
expected_result: list[list[Any]],
|
|
) -> None:
|
|
with sv.JSONSink(file_name) as sink:
|
|
sink.append(detections, custom_data)
|
|
sink.append(second_detections, second_custom_data)
|
|
|
|
assert_json_equal(file_name, expected_result)
|
|
|
|
|
|
def assert_json_equal(file_name, expected_rows):
|
|
with open(file_name) as file:
|
|
data = json.load(file)
|
|
assert data == expected_rows, (
|
|
f"Data in JSON file didn't match expected output: {data} != {expected_rows}"
|
|
)
|
|
|
|
os.remove(file_name)
|