From 936234d5b14070b3565d1bda112dba9a00c3fefc Mon Sep 17 00:00:00 2001 From: Alexander Alekhin Date: Sun, 3 Sep 2017 11:17:15 +0000 Subject: [PATCH] python(test): enable pylint checks for tests --- CMakeLists.txt | 1 + modules/python/test/test.py | 20 +++++++++----------- modules/python/test/test_calibration.py | 5 +---- modules/python/test/test_camshift.py | 2 +- modules/python/test/test_digits.py | 4 ++-- modules/python/test/test_facedetect.py | 2 -- modules/python/test/test_feature_homography.py | 2 +- modules/python/test/test_gaussian_mix.py | 4 ++-- modules/python/test/test_goodfeatures.py | 12 ++++++------ modules/python/test/test_houghcircles.py | 1 - modules/python/test/test_kmeans.py | 4 ++-- modules/python/test/test_letter_recog.py | 16 ++++++++-------- modules/python/test/test_lk_homography.py | 12 ++++++------ modules/python/test/test_lk_track.py | 4 ++-- modules/python/test/test_mser.py | 2 +- modules/python/test/test_peopledetect.py | 2 +- modules/python/test/test_shape.py | 4 ++-- modules/python/test/test_squares.py | 6 +++--- modules/python/test/test_stitching.py | 2 +- modules/python/test/tests_common.py | 2 +- 20 files changed, 50 insertions(+), 57 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index f2e28e5..2d288af 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -853,6 +853,7 @@ if(ANDROID OR NOT UNIX) endif() if(COMMAND ocv_pylint_finalize) + ocv_pylint_add_directory(${CMAKE_CURRENT_LIST_DIR}/modules/python/test) ocv_pylint_add_directory(${CMAKE_CURRENT_LIST_DIR}/samples/python) ocv_pylint_add_directory(${CMAKE_CURRENT_LIST_DIR}/samples/dnn) ocv_pylint_add_directory_recurse(${CMAKE_CURRENT_LIST_DIR}/samples/python/tutorial_code) diff --git a/modules/python/test/test.py b/modules/python/test/test.py index be3f821..222f321 100755 --- a/modules/python/test/test.py +++ b/modules/python/test/test.py @@ -75,7 +75,6 @@ class Hackathon244Tests(NewOpenCVTests): fd = cv2.FastFeatureDetector_create(30, True) img = self.get_sample("samples/data/right02.jpg", 0) img = cv2.medianBlur(img, 3) - imgc = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) keypoints = fd.detect(img) self.assertTrue(600 <= len(keypoints) <= 700) for kpt in keypoints: @@ -99,7 +98,6 @@ class Hackathon244Tests(NewOpenCVTests): np.random.seed(244) a = np.random.randn(npt,2).astype('float32')*50 + 150 - img = np.zeros((300, 300, 3), dtype='uint8') be = cv2.fitEllipse(a) br = cv2.minAreaRect(a) mc, mr = cv2.minEnclosingCircle(a) @@ -138,10 +136,10 @@ class Hackathon244Tests(NewOpenCVTests): def test_umat_handle(self): a_um = cv2.UMat(256, 256, cv2.CV_32F) - ctx_handle = cv2.UMat.context() # obtain context handle - queue_handle = cv2.UMat.queue() # obtain queue handle - a_handle = a_um.handle(cv2.ACCESS_READ) # obtain buffer handle - offset = a_um.offset # obtain buffer offset + _ctx_handle = cv2.UMat.context() # obtain context handle + _queue_handle = cv2.UMat.queue() # obtain queue handle + _a_handle = a_um.handle(cv2.ACCESS_READ) # obtain buffer handle + _offset = a_um.offset # obtain buffer offset def test_umat_matching(self): img1 = self.get_sample("samples/data/right01.jpg") @@ -186,11 +184,11 @@ class Hackathon244Tests(NewOpenCVTests): p0_umat = cv2.UMat(np.array(sorted(p0_umat.get(), key=lambda p: tuple(p[0])))) self.assertTrue(np.allclose(p0_umat.get(), p0)) - p1_mask_err = cv2.calcOpticalFlowPyrLK(img1, img2, p0, None) + _p1_mask_err = cv2.calcOpticalFlowPyrLK(img1, img2, p0, None) - p1_mask_err_umat0 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(img1, img2, p0_umat, None)) - p1_mask_err_umat1 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(cv2.UMat(img1), img2, p0_umat, None)) - p1_mask_err_umat2 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(img1, cv2.UMat(img2), p0_umat, None)) + _p1_mask_err_umat0 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(img1, img2, p0_umat, None)) + _p1_mask_err_umat1 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(cv2.UMat(img1), img2, p0_umat, None)) + _p1_mask_err_umat2 = map(cv2.UMat.get, cv2.calcOpticalFlowPyrLK(img1, cv2.UMat(img2), p0_umat, None)) # # results of OCL optical flow differs from CPU implementation, so result can not be easily compared # for p1_mask_err_umat in [p1_mask_err_umat0, p1_mask_err_umat1, p1_mask_err_umat2]: @@ -212,5 +210,5 @@ if __name__ == '__main__': except KeyError: print('Missing opencv extra repository. Some of tests may fail.') random.seed(0) - unit_argv = [sys.argv[0]] + other; + unit_argv = [sys.argv[0]] + other unittest.main(argv=unit_argv) diff --git a/modules/python/test/test_calibration.py b/modules/python/test/test_calibration.py index 584c7e6..f946a5b 100644 --- a/modules/python/test/test_calibration.py +++ b/modules/python/test/test_calibration.py @@ -16,8 +16,6 @@ from tests_common import NewOpenCVTests class calibration_test(NewOpenCVTests): def test_calibration(self): - - from glob import glob img_names = [] for i in range(1, 15): if i < 10: @@ -34,7 +32,6 @@ class calibration_test(NewOpenCVTests): obj_points = [] img_points = [] h, w = 0, 0 - img_names_undistort = [] for fn in img_names: img = self.get_sample(fn, 0) if img is None: @@ -53,7 +50,7 @@ class calibration_test(NewOpenCVTests): obj_points.append(pattern_points) # calculate camera distortion - rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None, flags = 0) + rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None, flags = 0) eps = 0.01 normCamEps = 10.0 diff --git a/modules/python/test/test_camshift.py b/modules/python/test/test_camshift.py index a824320..96ab58a 100644 --- a/modules/python/test/test_camshift.py +++ b/modules/python/test/test_camshift.py @@ -73,7 +73,7 @@ class camshift_test(NewOpenCVTests): prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) prob &= mask term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) - track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit) + _track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit) trackingRect = np.array(self.track_window) trackingRect[2] += trackingRect[0] diff --git a/modules/python/test/test_digits.py b/modules/python/test/test_digits.py index c7ac996..2643d05 100644 --- a/modules/python/test/test_digits.py +++ b/modules/python/test/test_digits.py @@ -71,7 +71,7 @@ class KNearest(StatModel): self.model.train(samples, cv2.ml.ROW_SAMPLE, responses) def predict(self, samples): - retval, results, neigh_resp, dists = self.model.findNearest(samples, self.k) + _retval, results, _neigh_resp, _dists = self.model.findNearest(samples, self.k) return results.ravel() class SVM(StatModel): @@ -147,7 +147,7 @@ class digits_test(NewOpenCVTests): samples = preprocess_hog(digits2) train_n = int(0.9*len(samples)) - digits_train, digits_test = np.split(digits2, [train_n]) + _digits_train, digits_test = np.split(digits2, [train_n]) samples_train, samples_test = np.split(samples, [train_n]) labels_train, labels_test = np.split(labels, [train_n]) errors = list() diff --git a/modules/python/test/test_facedetect.py b/modules/python/test/test_facedetect.py index 8d64fde..aa86a4f 100644 --- a/modules/python/test/test_facedetect.py +++ b/modules/python/test/test_facedetect.py @@ -23,8 +23,6 @@ from tests_common import NewOpenCVTests, intersectionRate class facedetect_test(NewOpenCVTests): def test_facedetect(self): - import sys, getopt - cascade_fn = self.repoPath + '/data/haarcascades/haarcascade_frontalface_alt.xml' nested_fn = self.repoPath + '/data/haarcascades/haarcascade_eye.xml' diff --git a/modules/python/test/test_feature_homography.py b/modules/python/test/test_feature_homography.py index 861ff92..c8c5dae 100644 --- a/modules/python/test/test_feature_homography.py +++ b/modules/python/test/test_feature_homography.py @@ -28,7 +28,7 @@ def intersectionRate(s1, s2): x1, y1, x2, y2 = s1 s1 = np.array([[x1, y1], [x2,y1], [x2, y2], [x1, y2]]) - area, intersection = cv2.intersectConvexConvex(s1, np.array(s2)) + area, _intersection = cv2.intersectConvexConvex(s1, np.array(s2)) return 2 * area / (cv2.contourArea(s1) + cv2.contourArea(np.array(s2))) from tests_common import NewOpenCVTests diff --git a/modules/python/test/test_gaussian_mix.py b/modules/python/test/test_gaussian_mix.py index 78a29ce..ac6ec43 100644 --- a/modules/python/test/test_gaussian_mix.py +++ b/modules/python/test/test_gaussian_mix.py @@ -15,7 +15,7 @@ import cv2 def make_gaussians(cluster_n, img_size): points = [] ref_distrs = [] - for i in xrange(cluster_n): + for _ in xrange(cluster_n): mean = (0.1 + 0.8*random.rand(2)) * img_size a = (random.rand(2, 2)-0.5)*img_size*0.1 cov = np.dot(a.T, a) + img_size*0.05*np.eye(2) @@ -44,7 +44,7 @@ class gaussian_mix_test(NewOpenCVTests): em.trainEM(points) means = em.getMeans() covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232 - found_distrs = zip(means, covs) + #found_distrs = zip(means, covs) matches_count = 0 diff --git a/modules/python/test/test_goodfeatures.py b/modules/python/test/test_goodfeatures.py index 5114ad8..5356eba 100644 --- a/modules/python/test/test_goodfeatures.py +++ b/modules/python/test/test_goodfeatures.py @@ -27,10 +27,10 @@ class TestGoodFeaturesToTrack_test(NewOpenCVTests): self.assertTrue(cv2.norm(results[t][i][0] - results2[t][i][0]) == 0) for t0,t1 in zip(threshes, threshes[1:]): - r0 = results[t0] - r1 = results[t1] - # Increasing thresh should make result list shorter - self.assertTrue(len(r0) > len(r1)) - # Increasing thresh should monly truncate result list - for i in range(len(r1)): + r0 = results[t0] + r1 = results[t1] + # Increasing thresh should make result list shorter + self.assertTrue(len(r0) > len(r1)) + # Increasing thresh should monly truncate result list + for i in range(len(r1)): self.assertTrue(cv2.norm(r1[i][0] - r0[i][0])==0) \ No newline at end of file diff --git a/modules/python/test/test_houghcircles.py b/modules/python/test/test_houghcircles.py index 318153a..23900d4 100644 --- a/modules/python/test/test_houghcircles.py +++ b/modules/python/test/test_houghcircles.py @@ -17,7 +17,6 @@ from tests_common import NewOpenCVTests def circleApproximation(circle): nPoints = 30 - phi = 0 dPhi = 2*pi / nPoints contour = [] for i in range(nPoints): diff --git a/modules/python/test/test_kmeans.py b/modules/python/test/test_kmeans.py index 4f886d9..512d535 100644 --- a/modules/python/test/test_kmeans.py +++ b/modules/python/test/test_kmeans.py @@ -21,7 +21,7 @@ def make_gaussians(cluster_n, img_size): points = [] ref_distrs = [] sizes = [] - for i in xrange(cluster_n): + for _ in xrange(cluster_n): mean = (0.1 + 0.8*random.rand(2)) * img_size a = (random.rand(2, 2)-0.5)*img_size*0.1 cov = np.dot(a.T, a) + img_size*0.05*np.eye(2) @@ -59,7 +59,7 @@ class kmeans_test(NewOpenCVTests): points, _, clusterSizes = make_gaussians(cluster_n, img_size) term_crit = (cv2.TERM_CRITERIA_EPS, 30, 0.1) - ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0) + _ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0) self.assertEqual(len(centers), cluster_n) diff --git a/modules/python/test/test_letter_recog.py b/modules/python/test/test_letter_recog.py index 574741f..83657ec 100644 --- a/modules/python/test/test_letter_recog.py +++ b/modules/python/test/test_letter_recog.py @@ -59,12 +59,12 @@ class RTrees(LetterStatModel): self.model = cv2.ml.RTrees_create() def train(self, samples, responses): - sample_n, var_n = samples.shape + #sample_n, var_n = samples.shape self.model.setMaxDepth(20) self.model.train(samples, cv2.ml.ROW_SAMPLE, responses.astype(int)) def predict(self, samples): - ret, resp = self.model.predict(samples) + _ret, resp = self.model.predict(samples) return resp.ravel() @@ -76,7 +76,7 @@ class KNearest(LetterStatModel): self.model.train(samples, cv2.ml.ROW_SAMPLE, responses) def predict(self, samples): - retval, results, neigh_resp, dists = self.model.findNearest(samples, k = 10) + _retval, results, _neigh_resp, _dists = self.model.findNearest(samples, k = 10) return results.ravel() @@ -85,7 +85,7 @@ class Boost(LetterStatModel): self.model = cv2.ml.Boost_create() def train(self, samples, responses): - sample_n, var_n = samples.shape + _sample_n, var_n = samples.shape new_samples = self.unroll_samples(samples) new_responses = self.unroll_responses(responses) var_types = np.array([cv2.ml.VAR_NUMERICAL] * var_n + [cv2.ml.VAR_CATEGORICAL, cv2.ml.VAR_CATEGORICAL], np.uint8) @@ -96,7 +96,7 @@ class Boost(LetterStatModel): def predict(self, samples): new_samples = self.unroll_samples(samples) - ret, resp = self.model.predict(new_samples) + _ret, resp = self.model.predict(new_samples) return resp.ravel().reshape(-1, self.class_n).argmax(1) @@ -113,7 +113,7 @@ class SVM(LetterStatModel): self.model.train(samples, cv2.ml.ROW_SAMPLE, responses.astype(int)) def predict(self, samples): - ret, resp = self.model.predict(samples) + _ret, resp = self.model.predict(samples) return resp.ravel() @@ -122,7 +122,7 @@ class MLP(LetterStatModel): self.model = cv2.ml.ANN_MLP_create() def train(self, samples, responses): - sample_n, var_n = samples.shape + _sample_n, var_n = samples.shape new_responses = self.unroll_responses(responses).reshape(-1, self.class_n) layer_sizes = np.int32([var_n, 100, 100, self.class_n]) @@ -136,7 +136,7 @@ class MLP(LetterStatModel): self.model.train(samples, cv2.ml.ROW_SAMPLE, np.float32(new_responses)) def predict(self, samples): - ret, resp = self.model.predict(samples) + _ret, resp = self.model.predict(samples) return resp.argmax(-1) from tests_common import NewOpenCVTests diff --git a/modules/python/test/test_lk_homography.py b/modules/python/test/test_lk_homography.py index 8e526d0..4dbcb79 100644 --- a/modules/python/test/test_lk_homography.py +++ b/modules/python/test/test_lk_homography.py @@ -27,8 +27,8 @@ feature_params = dict( maxCorners = 1000, blockSize = 19 ) def checkedTrace(img0, img1, p0, back_threshold = 1.0): - p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) - p0r, st, err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) + p1, _st, _err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) + p0r, _st, _err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) d = abs(p0-p0r).reshape(-1, 2).max(-1) status = d < back_threshold return p1, status @@ -77,11 +77,11 @@ class lk_homography_test(NewOpenCVTests): if len(self.p0) < 4: self.p0 = None continue - H, status = cv2.findHomography(self.p0, self.p1, cv2.RANSAC, 5.0) + _H, status = cv2.findHomography(self.p0, self.p1, cv2.RANSAC, 5.0) goodPointsInRect = 0 goodPointsOutsideRect = 0 - for (x0, y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]): + for (_x0, _y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]): if good: if isPointInRect((x1,y1), self.render.getCurrentRect()): goodPointsInRect += 1 @@ -91,6 +91,6 @@ class lk_homography_test(NewOpenCVTests): isForegroundHomographyFound = True self.assertGreater(float(goodPointsInRect) / (self.numFeaturesInRectOnStart + 1), 0.6) else: - p = cv2.goodFeaturesToTrack(frame_gray, **feature_params) + self.p0 = cv2.goodFeaturesToTrack(frame_gray, **feature_params) - self.assertEqual(isForegroundHomographyFound, True) \ No newline at end of file + self.assertEqual(isForegroundHomographyFound, True) diff --git a/modules/python/test/test_lk_track.py b/modules/python/test/test_lk_track.py index ccc67a5..655a92f 100644 --- a/modules/python/test/test_lk_track.py +++ b/modules/python/test/test_lk_track.py @@ -63,8 +63,8 @@ class lk_track_test(NewOpenCVTests): if len(self.tracks) > 0: img0, img1 = self.prev_gray, frame_gray p0 = np.float32([tr[-1][0] for tr in self.tracks]).reshape(-1, 1, 2) - p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) - p0r, st, err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) + p1, _st, _err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params) + p0r, _st, _err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params) d = abs(p0-p0r).reshape(-1, 2).max(-1) good = d < 1 new_tracks = [] diff --git a/modules/python/test/test_mser.py b/modules/python/test/test_mser.py index f66582e..a95f7ee 100644 --- a/modules/python/test/test_mser.py +++ b/modules/python/test/test_mser.py @@ -37,7 +37,7 @@ class mser_test(NewOpenCVTests): mserExtractor.setDelta(kDelta) np.random.seed(10) - for i in range(100): + for _i in range(100): use_big_image = int(np.random.rand(1,1)*7) != 0 invert = int(np.random.rand(1,1)*2) != 0 diff --git a/modules/python/test/test_peopledetect.py b/modules/python/test/test_peopledetect.py index fb0a9e9..cd70dc2 100644 --- a/modules/python/test/test_peopledetect.py +++ b/modules/python/test/test_peopledetect.py @@ -38,7 +38,7 @@ class peopledetect_test(NewOpenCVTests): img = self.get_sample(dirPath + sample, 0) - found, w = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05) + found, _w = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05) found_filtered = [] for ri, r in enumerate(found): for qi, q in enumerate(found): diff --git a/modules/python/test/test_shape.py b/modules/python/test/test_shape.py index ad0f0be..218b8e0 100644 --- a/modules/python/test/test_shape.py +++ b/modules/python/test/test_shape.py @@ -7,8 +7,8 @@ class shape_test(NewOpenCVTests): def test_computeDistance(self): - a = self.get_sample('samples/data/shape_sample/1.png', cv2.IMREAD_GRAYSCALE); - b = self.get_sample('samples/data/shape_sample/2.png', cv2.IMREAD_GRAYSCALE); + a = self.get_sample('samples/data/shape_sample/1.png', cv2.IMREAD_GRAYSCALE) + b = self.get_sample('samples/data/shape_sample/2.png', cv2.IMREAD_GRAYSCALE) _, ca, _ = cv2.findContours(a, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS) _, cb, _ = cv2.findContours(b, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_TC89_KCOS) diff --git a/modules/python/test/test_squares.py b/modules/python/test/test_squares.py index 214c64b..a6921ef 100644 --- a/modules/python/test/test_squares.py +++ b/modules/python/test/test_squares.py @@ -30,8 +30,8 @@ def find_squares(img): bin = cv2.Canny(gray, 0, 50, apertureSize=5) bin = cv2.dilate(bin, None) else: - retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY) - bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) + _retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY) + bin, contours, _hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) for cnt in contours: cnt_len = cv2.arcLength(cnt, True) cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True) @@ -44,7 +44,7 @@ def find_squares(img): return squares def intersectionRate(s1, s2): - area, intersection = cv2.intersectConvexConvex(np.array(s1), np.array(s2)) + area, _intersection = cv2.intersectConvexConvex(np.array(s1), np.array(s2)) return 2 * area / (cv2.contourArea(np.array(s1)) + cv2.contourArea(np.array(s2))) def filterSquares(squares, square): diff --git a/modules/python/test/test_stitching.py b/modules/python/test/test_stitching.py index 9a35357..d8faaec 100644 --- a/modules/python/test/test_stitching.py +++ b/modules/python/test/test_stitching.py @@ -11,7 +11,7 @@ class stitching_test(NewOpenCVTests): img2 = self.get_sample('stitching/a2.png') stitcher = cv2.createStitcher(False) - (result, pano) = stitcher.stitch((img1, img2)) + (_result, pano) = stitcher.stitch((img1, img2)) #cv2.imshow("pano", pano) #cv2.waitKey() diff --git a/modules/python/test/tests_common.py b/modules/python/test/tests_common.py index 17ef0dc..7a7e3ba 100644 --- a/modules/python/test/tests_common.py +++ b/modules/python/test/tests_common.py @@ -70,7 +70,7 @@ def intersectionRate(s1, s2): x1, y1, x2, y2 = s2 s2 = np.array([[x1, y1], [x2,y1], [x2, y2], [x1, y2]]) - area, intersection = cv2.intersectConvexConvex(s1, s2) + area, _intersection = cv2.intersectConvexConvex(s1, s2) return 2 * area / (cv2.contourArea(s1) + cv2.contourArea(s2)) def isPointInRect(p, rect): -- 2.7.4