Tests (#37)

* add py test

* update dependencies and markers

* Update ci.yml

* fix linting

* trying with editable install for cov

* fix code smells

* fix code smells

Co-authored-by: xianghe ma <maxianghe@outlook.com>

.github/workflows/ci.yml

@@ -27,13 +27,13 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install .
+        python -m pip install -e .
     - name: Run pytest
       run: |
         cd misinformation
-        python -m pytest -s --cov=. --cov-report=xml
+        python -m pytest -s -m "not imageai" --cov=. --cov-report=xml
     - name: Upload coverage
-      uses: codecov/codecov-action@v1
+      uses: codecov/codecov-action@v3
       with:
         fail_ci_if_error: true
         files: misinformation/coverage.xml

misinformation/test/data/example_analysis_faces.json

@@ -0,0 +1 @@
+{"IMG_2746": {"filename": "./test/data/IMG_2746.png", "face": "Yes", "multiple_faces": "Yes", "no_faces": 11, "wears_mask": ["No", "No", "Yes"], "age": [36, 35, 33], "gender": ["Man", "Man", "Man"], "race": ["white", "white", null], "emotion": [["sad", 73.24262697950762], ["fear", 84.20094847679138], null], "emotion (category)": ["Negative", "Negative", null]}}

misinformation/test/data/example_analysis_objects.json

@@ -0,0 +1 @@
+{"IMG_2746": {"filename": "./test/data/IMG_2809.png", "person": "yes", "bicycle": "no", "car": "yes", "motorcycle": "no", "airplane": "no", "bus": "yes", "train": "no", "truck": "no", "boat": "no", "traffic light": "no", "cell phone": "no"}}

misinformation/test/data/example_objects_cvlib.json

@@ -1,14 +1 @@
-{
+{"filename": "./test/data/IMG_2809.png", "person": "yes", "bicycle": "no", "car": "yes", "motorcycle": "no", "airplane": "no", "bus": "yes", "train": "no", "truck": "no", "boat": "no", "traffic light": "no", "cell phone": "no"}
-    "filename": "./test/data/IMG_2809.png", 
-    "person": "yes", 
-    "bicycle": "no", 
-    "car": "yes", 
-    "motorcycle": "no", 
-    "airplane": "no", 
-    "bus": "yes", 
-    "train": "no", 
-    "truck": "no", 
-    "boat": "no", 
-    "traffic light": "no", 
-    "cell phone": "no"
-}

misinformation/test/data/example_objects_imageai.json

@@ -0,0 +1,14 @@
+{
+    "filename": "./test/data/IMG_2809.png",
+    "person": "yes",
+    "bicycle": "yes",
+    "car": "yes",
+    "motorcycle": "no",
+    "airplane": "no",
+    "bus": "yes",
+    "train": "no",
+    "truck": "no",
+    "boat": "no",
+    "traffic light": "no",
+    "cell phone": "no"
+}

misinformation/test/data/example_objects_imageai.txt

@@ -1 +0,0 @@
-{'image_objects': {'filename': './misinformation/test/data/IMG_2809.png', 'person': 'yes', 'bicycle': 'yes', 'car': 'yes', 'motorcycle': 'no', 'airplane': 'no', 'bus': 'yes', 'train': 'no', 'truck': 'no', 'boat': 'no', 'traffic light': 'no', 'cell phone': 'no'}}

misinformation/test/pytest.ini

@@ -0,0 +1,3 @@
+[pytest]
+markers =
+    imageai: mark a test related to imageai.

misinformation/test/test_cropposts.py

@@ -0,0 +1,63 @@
+import misinformation.cropposts as crpo
+import numpy as np
+from PIL import Image
+
+TEST_IMAGE_1 = "./test/data/pic1.png"
+TEST_IMAGE_2 = "./test/data/pic2.png"
+
+
+def test_matching_points():
+    ref_view = np.array(Image.open(TEST_IMAGE_2))
+    view = np.array(Image.open(TEST_IMAGE_1))
+    filtered_matches, kp1, kp2 = crpo.matching_points(ref_view, view)
+    assert len(filtered_matches) > 0
+
+
+def test_kp_from_matches():
+    ref_view = np.array(Image.open(TEST_IMAGE_2))
+    view = np.array(Image.open(TEST_IMAGE_1))
+    filtered_matches, kp1, kp2 = crpo.matching_points(ref_view, view)
+    kp1, kp2 = crpo.kp_from_matches(filtered_matches, kp1, kp2)
+
+    assert kp1.shape[0] == len(filtered_matches)
+    assert kp2.shape[0] == len(filtered_matches)
+    assert kp1.shape[1] == 2
+    assert kp2.shape[1] == 2
+
+
+def test_compute_crop_corner():
+    ref_view = np.array(Image.open(TEST_IMAGE_2))
+    view = np.array(Image.open(TEST_IMAGE_1))
+    filtered_matches, kp1, kp2 = crpo.matching_points(ref_view, view)
+    corner = crpo.compute_crop_corner(filtered_matches, kp1, kp2)
+    print(view.shape)
+    print(corner)
+    assert corner is not None
+    v, h = corner
+    assert 0 <= v < view.shape[0]
+    assert 0 <= h < view.shape[0]
+
+
+def test_crop_posts_image():
+    ref_view = np.array(Image.open(TEST_IMAGE_2))
+    view = np.array(Image.open(TEST_IMAGE_1))
+    rte = crpo.crop_posts_image(ref_view, view)
+    assert rte is not None
+    crop_view, match_num = rte
+    assert match_num > 0
+    assert crop_view.shape[0] * crop_view.shape[1] <= view.shape[0] * view.shape[1]
+
+
+def test_crop_posts_from_refs():
+    ref_view = np.array(Image.open(TEST_IMAGE_2))
+    view = np.array(Image.open(TEST_IMAGE_1))
+    ref_views = [ref_view]
+    crop_view = crpo.crop_posts_from_refs(ref_views, view)
+    assert crop_view.shape[0] * crop_view.shape[1] <= view.shape[0] * view.shape[1]
+
+
+def test_get_file_list():
+    ref_list = []
+    ref_dir = "./test/data"
+    ref_list = crpo.get_file_list(ref_dir, ref_list, ext="png")
+    assert len(ref_list) > 0

misinformation/test/test_display.py

@@ -0,0 +1,33 @@
+import json
+from misinformation.display import explore_analysis
+from pytest import approx
+
+
+def test_explore_analysis_faces():
+    mydict = {"IMG_2746": {"filename": "./test/data/IMG_2746.png"}}
+    explore_analysis(mydict, identify="faces")
+    with open("./test/data/example_analysis_faces.json", "r") as file:
+        outs = json.load(file)
+
+    for im_key in mydict.keys():
+        sub_dict = mydict[im_key]
+        for key in sub_dict.keys():
+            if key != "emotion":
+                assert sub_dict[key] == outs[im_key][key]
+        # json can't handle tuples natively
+        for i in range(0, len(sub_dict["emotion"])):
+            temp = (
+                list(sub_dict["emotion"][i])
+                if type(sub_dict["emotion"][i]) == tuple
+                else sub_dict["emotion"][i]
+            )
+            assert approx(temp) == outs[im_key]["emotion"][i]
+
+
+def test_explore_analysis_objects():
+    mydict = {"IMG_2746": {"filename": "./test/data/IMG_2809.png"}}
+    explore_analysis(mydict, identify="objects")
+    with open("./test/data/example_analysis_objects.json", "r") as file:
+        outs = json.load(file)
+
+    assert str(mydict) == str(outs)

misinformation/test/test_objects.py

@@ -1,9 +1,17 @@
 import json
 import pytest
-import misinformation
 import misinformation.objects as ob
 import misinformation.objects_cvlib as ob_cvlib
 
+# import misinformation.objects_imageai as ob_iai
+
+OBJECT_1 = "cell phone"
+OBJECT_2 = "motorcycle"
+OBJECT_3 = "traffic light"
+TEST_IMAGE_1 = "./test/data/IMG_2809.png"
+JSON_1 = "./test/data/example_objects_cvlib.json"
+JSON_2 = "./test/data/example_objects_imageai.json"
+
 
 @pytest.fixture()
 def default_objects():
@@ -11,7 +19,7 @@ def default_objects():
 
 
 def test_objects_from_cvlib(default_objects):
-    objects_list = ["cell phone", "motorcycle", "traffic light"]
+    objects_list = [OBJECT_1, OBJECT_2, OBJECT_3]
     objects = ob_cvlib.objects_from_cvlib(objects_list)
     out_objects = default_objects
     for obj in objects_list:
@@ -21,11 +29,113 @@ def test_objects_from_cvlib(default_objects):
 
 
 def test_analyse_image_cvlib():
-    mydict = {"filename": "./test/data/IMG_2809.png"}
+    mydict = {"filename": TEST_IMAGE_1}
     ob_cvlib.ObjectCVLib().analyse_image(mydict)
 
-    with open("./test/data/example_objects_cvlib.json", "r") as file:
+    with open(JSON_1, "r") as file:
         out_dict = json.load(file)
     for key in mydict.keys():
-        print(key)
         assert mydict[key] == out_dict[key]
+
+
+def test_init_default_objects():
+    default_obj_list = [
+        "person",
+        "bicycle",
+        "car",
+        OBJECT_2,
+        "airplane",
+        "bus",
+        "train",
+        "truck",
+        "boat",
+        OBJECT_3,
+        OBJECT_1,
+    ]
+    init_objects = ob_cvlib.init_default_objects()
+    for obj in default_obj_list:
+        assert init_objects[obj] == "no"
+
+
+def test_analyse_image_from_file_cvlib():
+    file_path = TEST_IMAGE_1
+    objs = ob_cvlib.ObjectCVLib().analyse_image_from_file(file_path)
+
+    with open(JSON_1, "r") as file:
+        out_dict = json.load(file)
+    for key in objs.keys():
+        assert objs[key] == out_dict[key]
+
+
+def test_detect_objects_cvlib():
+    file_path = TEST_IMAGE_1
+    objs = ob_cvlib.ObjectCVLib().detect_objects_cvlib(file_path)
+
+    with open(JSON_1, "r") as file:
+        out_dict = json.load(file)
+    for key in objs.keys():
+        assert objs[key] == out_dict[key]
+
+
+@pytest.mark.imageai
+def test_objects_from_imageai(default_objects):
+    objects_list = [OBJECT_1, OBJECT_2, OBJECT_3]
+    objs_input = [
+        {"name": OBJECT_1},
+        {"name": OBJECT_2},
+        {"name": OBJECT_3},
+    ]
+    objects = ob_iai.objects_from_imageai(objs_input)  # noqa: F821
+    out_objects = default_objects
+    for obj in objects_list:
+        out_objects[obj] = "yes"
+
+    assert str(objects) == str(out_objects)
+
+
+@pytest.mark.imageai
+def test_analyse_image_from_file_imageai():
+    file_path = TEST_IMAGE_1
+    objs = ob_iai.ObjectImageAI().analyse_image_from_file(file_path)  # noqa: F821
+
+    with open(JSON_2, "r") as file:
+        out_dict = json.load(file)
+    for key in objs.keys():
+        assert objs[key] == out_dict[key]
+
+
+@pytest.mark.imageai
+def test_detect_objects_imageai():
+    file_path = TEST_IMAGE_1
+    objs = ob_iai.ObjectImageAI().detect_objects_imageai(file_path)  # noqa: F821
+
+    with open(JSON_2, "r") as file:
+        out_dict = json.load(file)
+    for key in objs.keys():
+        assert objs[key] == out_dict[key]
+
+
+@pytest.mark.imageai
+def test_analyse_image_imageai():
+    mydict = {"filename": TEST_IMAGE_1}
+    ob_iai.ObjectImageAI().analyse_image(mydict)  # noqa: F821
+    with open(JSON_2, "r") as file:
+        out_dict = json.load(file)
+    for key in mydict.keys():
+        assert mydict[key] == out_dict[key]
+
+
+def test_set_keys(default_objects):
+    mydict = {"filename": TEST_IMAGE_1}
+    key_objs = ob.ObjectDetector(mydict).set_keys()
+    assert str(default_objects) == str(key_objs)
+
+
+def test_analyse_image():
+    mydict = {"filename": TEST_IMAGE_1}
+    ob.ObjectDetector.set_client_to_cvlib()
+    ob.ObjectDetector(mydict).analyse_image()
+    with open(JSON_1, "r") as file:
+        out_dict = json.load(file)
+
+    assert str(mydict) == str(out_dict)

pyproject.toml

@@ -37,6 +37,9 @@ dependencies = [
     "openpyxl",
     "pytest",
     "pytest-cov",
+    "matplotlib",
+    "pytest",
+    "opencv-contrib-python",
 ]
 
 [project.scripts]

requirements.txt

@@ -14,3 +14,5 @@ keras
 openpyxl
 pytest
 pytest-cov
+matplotlib
+opencv-contrib-python