efficientnet-b0-mlop1 / test /test_api.py
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import pytest
from fastapi.testclient import TestClient
from app.main import app
import os
import glob
client = TestClient(app)
def get_sample_image_path():
image_dir = os.path.join("image", "Khao_phat")
files = glob.glob(os.path.join(image_dir, "*.jpg")) + \
glob.glob(os.path.join(image_dir, "*.png")) + \
glob.glob(os.path.join(image_dir, "*.jpeg"))
if not files:
pytest.fail("No sample images found")
return files[0]
def test_predict_api_returns_valid_json():
image_path = get_sample_image_path()
with open(image_path, "rb") as f:
response = client.post(
"/predict",
data={"model_type": "onnx"},
files={"file": ("test.jpg", f, "image/jpeg")}
)
assert response.status_code == 200
json_data = response.json()
# 1) เช็คว่าเป็น JSON structure ถูกต้อง
assert isinstance(json_data, dict)
assert "prediction_class_id" in json_data
assert "confidence_score" in json_data
assert "prediction_class_name" in json_data
def test_predict_model_returns_prediction():
image_path = get_sample_image_path()
with open(image_path, "rb") as f:
response = client.post(
"/predict",
data={"model_type": "onnx"},
files={"file": ("test.jpg", f, "image/jpeg")}
)
assert response.status_code == 200
json_data = response.json()
# 2) เช็คว่า model “ทำนายได้จริง”
assert json_data["prediction_class_name"] is not None
assert json_data["confidence_score"] >= 0