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import json
import os
import requests
import time
import pytest
from io import BytesIO
from pathlib import Path
from PIL import Image
from requests_toolbelt.multipart.encoder import MultipartEncoder
PIXEL_TOLERANCE = 2
CONFIDENCE_TOLERANCE = 0.005
TIME_TOLERANCE = 0.75
api_key = os.environ.get("API_KEY")
port = os.environ.get("PORT", 9001)
base_url = os.environ.get("BASE_URL", "http://localhost")
def bool_env(val):
if isinstance(val, bool):
return val
return val.lower() in ["true", "1", "t", "y", "yes"]
def model_add(test, port=9001, api_key="", base_url="http://localhost"):
return requests.post(
f"{base_url}:{port}/{test['project']}/{test['version']}?"
+ "&".join(
[
f"api_key={api_key}",
f"confidence={test['confidence']}",
f"overlap={test['iou_threshold']}",
f"image={test['image_url']}",
]
)
)
def legacy_infer_with_image_url(
test, port=9001, api_key="", base_url="http://localhost"
):
return (
requests.post(
f"{base_url}:{port}/{test['project']}/{test['version']}?"
+ "&".join(
[
f"api_key={api_key}",
f"confidence={test['confidence']}",
f"overlap={test['iou_threshold']}",
f"image={test['image_url']}",
]
)
),
"url",
)
def legacy_infer_with_base64_image(
test, port=9001, api_key="", base_url="http://localhost"
):
buffered = BytesIO()
test["pil_image"].save(buffered, quality=100, format="PNG")
img_str = base64.b64encode(buffered.getvalue())
img_str = img_str.decode("ascii")
if test.get("simulate_rfwidget_upload", False):
img_str = f"data:image/jpeg;base64,{img_str}"
return (
requests.post(
f"{base_url}:{port}/{test['project']}/{test['version']}?"
+ "&".join(
[
f"api_key={api_key}",
f"confidence={test['confidence']}",
f"overlap={test['iou_threshold']}",
]
),
data=img_str,
headers={"Content-Type": "application/x-www-form-urlencoded"},
),
"base64",
)
def legacy_infer_with_multipart_form_image(
test, port=9001, api_key="", base_url="http://localhost"
):
buffered = BytesIO()
test["pil_image"].save(buffered, quality=100, format="JPEG")
m = MultipartEncoder(
fields={"file": ("original.jpeg", buffered.getvalue(), "image/jpeg")}
)
return (
requests.post(
f"{base_url}:{port}/{test['project']}/{test['version']}?"
+ "&".join(
[
f"api_key={api_key}",
f"confidence={test['confidence']}",
f"overlap={test['iou_threshold']}",
]
),
data=m,
headers={"Content-Type": m.content_type},
),
"multipart_form",
)
def infer_request_with_image_url(
test, port=9001, api_key="", base_url="http://localhost"
):
payload = {
"model_id": f"{test['project']}/{test['version']}",
"image": {
"type": "url",
"value": test["image_url"],
},
"confidence": test["confidence"],
"iou_threshold": test["iou_threshold"],
"api_key": api_key,
}
return (
requests.post(
f"{base_url}:{port}/infer/{test['type']}",
json=payload,
),
"url",
)
def infer_request_with_base64_image(
test, port=9001, api_key="", base_url="http://localhost"
):
buffered = BytesIO()
test["pil_image"].save(buffered, quality=100, format="PNG")
img_str = base64.b64encode(buffered.getvalue())
img_str = img_str.decode("ascii")
payload = {
"model_id": f"{test['project']}/{test['version']}",
"image": {
"type": "base64",
"value": img_str,
},
"confidence": test["confidence"],
"iou_threshold": test["iou_threshold"],
"api_key": api_key,
}
return (
requests.post(
f"{base_url}:{port}/infer/{test['type']}",
json=payload,
),
"base64",
)
def compare_detection_response(
response, expected_response, type="object_detection", multilabel=False
):
try:
assert "time" in response
except AssertionError:
raise ValueError(f"Invalid response: {response}, Missing 'time' field.")
# try:
# assert response["time"] == pytest.approx(
# expected_response["time"], rel=None, abs=TIME_TOLERANCE
# )
# except AssertionError:
# raise ValueError(
# f"Invalid response: {response}, 'time' field does not match expected value. Expected {expected_response['time']}, got {response['time']}."
# )
try:
assert "image" in response
except AssertionError:
raise ValueError(f"Invalid response: {response}, Missing 'image' field.")
try:
assert response["image"]["width"] == expected_response["image"]["width"]
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'image' field does not match expected value. Expected {expected_response['image']['width']}, got {response['image']['width']}."
)
try:
assert response["image"]["height"] == expected_response["image"]["height"]
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'image' field does not match expected value. Expected {expected_response['image']['height']}, got {response['image']['height']}."
)
try:
assert "predictions" in response
except AssertionError:
raise ValueError(f"Invalid response: {response}, Missing 'predictions' field.")
try:
assert len(response["predictions"]) == len(expected_response["predictions"])
except AssertionError:
raise ValueError(
f"Invalid response: {response}, number of predictions does not match expected value. Expected {len(expected_response['predictions'])} predictions, got {len(response['predictions'])}."
)
if type in ["object_detection", "instance_segmentation"]:
for i, prediction in enumerate(response["predictions"]):
try:
assert prediction["x"] == pytest.approx(
expected_response["predictions"][i]["x"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'x' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['x']}, got {prediction['x']}."
)
try:
assert prediction["y"] == pytest.approx(
expected_response["predictions"][i]["y"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'y' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['y']}, got {prediction['y']}."
)
try:
assert prediction["width"] == pytest.approx(
expected_response["predictions"][i]["width"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'width' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['width']}, got {prediction['width']}."
)
try:
assert prediction["height"] == pytest.approx(
expected_response["predictions"][i]["height"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'height' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['height']}, got {prediction['height']}."
)
try:
assert prediction["confidence"] == pytest.approx(
expected_response["predictions"][i]["confidence"],
rel=None,
abs=CONFIDENCE_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'confidence' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['confidence']}, got {prediction['confidence']}."
)
try:
assert (
prediction["class"] == expected_response["predictions"][i]["class"]
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'class' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['class']}, got {prediction['class']}."
)
if type == "instance_segmentation":
try:
assert "points" in prediction
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'points' field for prediction {i}."
)
for j, point in enumerate(prediction["points"]):
try:
assert point["x"] == pytest.approx(
expected_response["predictions"][i]["points"][j]["x"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'x' field does not match expected value for prediction {i}, point {j}. Expected {expected_response['predictions'][i]['points'][j]['x']}, got {point['x']}."
)
try:
assert point["y"] == pytest.approx(
expected_response["predictions"][i]["points"][j]["y"],
rel=None,
abs=PIXEL_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'y' field does not match expected value for prediction {i}, point {j}. Expected {expected_response['predictions'][i]['points'][j]['y']}, got {point['y']}."
)
elif type == "classification":
if multilabel:
for class_name, confidence in response["predictions"].items():
try:
assert class_name in expected_response["predictions"]
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Unexpected class {class_name}. Expected classes: {expected_response['predictions'].keys()}."
)
try:
assert "confidence" in confidence
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'confidence' field for class {class_name}."
)
try:
assert confidence["confidence"] == pytest.approx(
expected_response["predictions"][class_name]["confidence"],
rel=None,
abs=CONFIDENCE_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'confidence' field does not match expected value for class {class_name}. Expected {expected_response['predictions'][class_name]['confidence']}, got {confidence['confidence']}."
)
try:
assert "predicted_classes" in response
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'predicted_classes' field."
)
for class_name in response["predicted_classes"]:
try:
assert class_name in expected_response["predictions"]
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Unexpected class {class_name}. Expected classes: {expected_response['predicted_classes']}."
)
else:
try:
assert "top" in response
except AssertionError:
raise ValueError(f"Invalid response: {response}, Missing 'top' field.")
try:
assert response["top"] == expected_response["top"]
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'top' field does not match expected value. Expected {expected_response['top']}, got {response['top']}."
)
try:
assert "confidence" in response
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'confidence' field."
)
try:
assert response["confidence"] == pytest.approx(
expected_response["confidence"],
rel=None,
abs=CONFIDENCE_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'confidence' field does not match expected value. Expected {expected_response['confidence']}, got {response['confidence']}."
)
for i, prediction in enumerate(response["predictions"]):
try:
assert "class" in prediction
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'class' field for prediction {i}."
)
try:
assert "confidence" in prediction
except AssertionError:
raise ValueError(
f"Invalid response: {response}, Missing 'confidence' field for prediction {i}."
)
try:
assert prediction["confidence"] == pytest.approx(
expected_response["predictions"][i]["confidence"],
rel=None,
abs=CONFIDENCE_TOLERANCE,
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'confidence' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['confidence']}, got {prediction['confidence']}."
)
try:
assert (
prediction["class"]
== expected_response["predictions"][i]["class"]
)
except AssertionError:
raise ValueError(
f"Invalid response: {response}, 'class' field does not match expected value for prediction {i}. Expected {expected_response['predictions'][i]['class']}, got {prediction['class']}."
)
with open(os.path.join(Path(__file__).resolve().parent, "tests.json"), "r") as f:
TESTS = json.load(f)
INFER_RESPONSE_FUNCTIONS = [
infer_request_with_image_url,
infer_request_with_base64_image,
legacy_infer_with_image_url,
legacy_infer_with_base64_image,
legacy_infer_with_multipart_form_image,
]
SKIP_YOLOV8_TEST = bool_env(os.getenv("SKIP_YOLOV8_TEST", False))
DETECTION_TEST_PARAMS = []
for test in TESTS:
if "expected_response" in test:
if not SKIP_YOLOV8_TEST or "YOLOv8" not in test["description"]:
for res_func in INFER_RESPONSE_FUNCTIONS:
DETECTION_TEST_PARAMS.append((test, res_func))
@pytest.mark.parametrize("test,res_function", DETECTION_TEST_PARAMS)
def test_detection(test, res_function):
try:
try:
pil_image = Image.open(
requests.get(test["image_url"], stream=True).raw
).convert("RGB")
test["pil_image"] = pil_image
except Exception as e:
raise ValueError(f"Unable to load image from URL: {test['image_url']}")
response, image_type = res_function(
test, port, api_key=os.getenv(f"{test['project'].replace('-','_')}_API_KEY")
)
try:
response.raise_for_status()
except requests.exceptions.HTTPError as e:
raise ValueError(f"Failed to make request to {res_function.__name__}: {e}")
try:
data = response.json()
except ValueError:
raise ValueError(f"Invalid JSON response: {response.text}")
try:
assert "expected_response" in test
except AssertionError:
raise ValueError(
f"Invalid test: {test}, Missing 'expected_response' field in test."
)
try:
assert image_type in test["expected_response"]
except AssertionError:
raise ValueError(
f"Invalid test: {test}, Missing 'expected_response' field for image type {image_type}."
)
if not bool_env(os.getenv("FUNCTIONAL", False)):
compare_detection_response(
data,
test["expected_response"][image_type],
type=test["type"],
multilabel=test.get("multi_label", False),
)
print(
"\u2713"
+ f" Test {test['project']}/{test['version']} passed with {res_function.__name__}."
)
except Exception as e:
raise Exception(f"Error in test {test['description']}: {e}")
@pytest.fixture(scope="session", autouse=True)
def setup():
try:
res = requests.get(f"{base_url}:{port}")
res.raise_for_status()
success = True
except:
success = False
waited = 0
while not success:
print("Waiting for server to start...")
time.sleep(5)
waited += 5
try:
res = requests.get(f"{base_url}:{port}")
res.raise_for_status()
success = True
except:
success = False
if waited > 30:
raise Exception("Test server failed to start")
if __name__ == "__main__":
# This helps figure out which test is failing
for i, param in enumerate(DETECTION_TEST_PARAMS):
print(i, param[0]["project"], param[0]["version"], param[1].__name__)
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