Merge pull request #5 from HunyyDev/NMPhap/testing

app/routers/test_image.py

@@ -0,0 +1,68 @@
+import os
+import mmcv
+import numpy as np
+from app.routers.image import inferenceImage
+import pytest
+import pytest
+from fastapi.testclient import TestClient
+from app.main import app
+
+@pytest.fixture
+def client():
+    client = TestClient(app, "http://0.0.0.0:3000")
+    yield client
+class TestImageRoute():
+    img = mmcv.imread('demo.jpg')
+    url = "http://0.0.0.0:3000/image"
+    def test_inferenceImage(self):
+        bboxes, labels = inferenceImage(mmcv.imread('demo.jpg'), 0.3, True)
+        assert len(bboxes.tolist()) > 0 and len(labels.tolist()) > 0 and len(bboxes.tolist()) == len(labels.tolist())
+        result = inferenceImage(self.img, 0.3)
+        assert type(result) is np.ndarray and result.shape == self.img.shape
+    def test_ImageAPI(self, client):
+        payload = {}
+        files=[
+        ('file',('demo.jpg',open('demo.jpg','rb'),'image/jpeg'))
+        ]
+        headers = {
+        'accept': 'application/json'
+        }
+        response = client.request("POST", "image", headers=headers, data=payload, files=files)
+        result = mmcv.imfrombytes(response.read())
+        assert response.status_code == 200 and result.shape == self.img.shape
+    def test_ImageAPI_one_channel_array(self, client):
+        np.zeros((1,640,640)).dump("one_channel.jpg")
+        payload = {}
+        files=[
+            ('file', ("demo.jpg",open("one_channel.jpg", "rb"),'image/jpeg'))
+        ]
+        headers = {
+        'accept': 'application/json'
+        }
+        response = client.request("POST", "image", headers=headers, data=payload, files=files)
+        assert response.status_code != 200
+    def test_ImageAPIWithThresHold(self, client):
+        payload = {}
+        files=[
+        ('file',('demo.jpg',open('demo.jpg','rb'),'image/jpeg'))
+        ]
+        headers = {
+        'accept': 'application/json'
+        }
+        response = client.request("POST", "image?threshold=1&raw=True", headers=headers, data=payload, files=files)
+        thresHold = 0.4
+        assert response.status_code == 200 # The result with threshold equal 0 is 0 
+        # No detected object has 100% accuracy
+        assert len(response.json()["labels"]) == 0
+        payload = {}
+        files=[
+        ('file',('demo.jpg',open('demo.jpg','rb'),'image/jpeg'))
+        ]
+        headers = {
+        'accept': 'application/json'
+        }
+        response = client.request("POST", "image?threshold=" + str(thresHold) + "&raw=True", headers=headers, data=payload, files=files)
+        assert response.status_code == 200
+        for bbox in response.json()['bboxes']:
+            assert bbox[4] >= thresHold
+