def test_random_with_same_aspect(): # rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) # if not any((rect.intersects_pixelrectangle(pr) for pr in excl_info)): # # Test random_with_same_aspect: # img_path = neg_regions[0].fname # img = cv2.imread(img_path) window_dims = (300, 200) img = np.zeros((500, 500, 3), np.uint8) h, w = img.shape[:2] imsize = (w, h) rects = [] for i in range(10000): rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) rects.append(rect) clone = img.copy() training.cvDrawRectangle(clone, rect, (255, 0, 0), 2) # Test moved_to_clear: new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) training.cvDrawRectangle(clone, new_rect, (0, 255, 0), 2) moved_rect = new_rect.moved_to_clear(rect) training.cvDrawRectangle(clone, moved_rect, (0, 0, 255), 2) print rect.intersects_pixelrectangle(moved_rect) # Test intersects_pixelrectangle: # for i in range(200): # new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) # col = (0, 0, 255) if rect.intersects_pixelrectangle(new_rect) else (255, 255, 255) # if not rect.intersects_pixelrectangle(new_rect): # training.cvDrawRectangle(clone, new_rect, col, 2) cv2.imshow("img", clone) while True: key = cv2.waitKey(1) & 0xFF # if key == 27: # ESC key # cv2.destroyAllWindows() # return if key != 255: break print "Saving histogram..." from cardetection.carutils.plotting import saveHistogram aspects = map(lambda r: r.w, rects) saveHistogram("region-aspects.pdf", aspects, bins=20) print "Saved!"
def test_random_with_same_aspect(): # rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) # if not any((rect.intersects_pixelrectangle(pr) for pr in excl_info)): # # Test random_with_same_aspect: # img_path = neg_regions[0].fname # img = cv2.imread(img_path) window_dims = (300, 200) img = np.zeros((500, 500, 3), np.uint8) h, w = img.shape[:2] imsize = (w, h) rects = [] for i in range(10000): rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) rects.append(rect) clone = img.copy() training.cvDrawRectangle(clone, rect, (255, 0, 0), 2) # Test moved_to_clear: new_rect = gm.PixelRectangle.random_with_same_aspect( window_dims, imsize) training.cvDrawRectangle(clone, new_rect, (0, 255, 0), 2) moved_rect = new_rect.moved_to_clear(rect) training.cvDrawRectangle(clone, moved_rect, (0, 0, 255), 2) print rect.intersects_pixelrectangle(moved_rect) # Test intersects_pixelrectangle: # for i in range(200): # new_rect = gm.PixelRectangle.random_with_same_aspect(window_dims, imsize) # col = (0, 0, 255) if rect.intersects_pixelrectangle(new_rect) else (255, 255, 255) # if not rect.intersects_pixelrectangle(new_rect): # training.cvDrawRectangle(clone, new_rect, col, 2) cv2.imshow('img', clone) while True: key = cv2.waitKey(1) & 0xFF # if key == 27: # ESC key # cv2.destroyAllWindows() # return if key != 255: break print 'Saving histogram...' from cardetection.carutils.plotting import saveHistogram aspects = map(lambda r: r.w, rects) saveHistogram('region-aspects.pdf', aspects, bins=20) print 'Saved!'
# for img_path in training.sampleTrainingImages(positive_dir, ['.*'], None, require_bboxes=True, bbinfo_dir=bbinfo_dir): # key = img_path.split('/')[-1] # rects_str = global_info[key] # rects = utils.rectangles_from_cache_string(rects_str) # for rect in rects: # all_rects.append(rect) # # # aspects = map(lambda rect: rect.h/float(rect.w), all_rects) kitti_base = '/Users/mitchell/data/kitti/' category_types = ['Car', 'Van'] pos_labels = kitti.getPositiveImageLabels(kitti_base, category_types) aspects = map(lambda l: l.aspect, pos_labels) saveHistogram('aspects.pdf', aspects) plt.close() # angles = map(lambda l: l.alpha*180.0/np.pi, pos_labels) angles = map(lambda l: l.ry * 180.0 / np.pi, pos_labels) # angles = map(lambda l: l.ry, pos_labels) saveHistogram('angles.pdf', angles) shape = (64, 64) aspect = shape[0] / float(shape[1]) angle = -90 angleRange = 5 aspectRange = 0.5 filtered = pos_labels filtered = filter(
# for img_path in training.sampleTrainingImages(positive_dir, ['.*'], None, require_bboxes=True, bbinfo_dir=bbinfo_dir): # key = img_path.split('/')[-1] # rects_str = global_info[key] # rects = utils.rectangles_from_cache_string(rects_str) # for rect in rects: # all_rects.append(rect) # # # aspects = map(lambda rect: rect.h/float(rect.w), all_rects) kitti_base = '/Users/mitchell/data/kitti/' category_types = ['Car', 'Van'] pos_labels = kitti.getPositiveImageLabels(kitti_base, category_types) aspects = map(lambda l: l.aspect, pos_labels) saveHistogram('aspects.pdf', aspects) plt.close() # angles = map(lambda l: l.alpha*180.0/np.pi, pos_labels) angles = map(lambda l: l.ry*180.0/np.pi, pos_labels) # angles = map(lambda l: l.ry, pos_labels) saveHistogram('angles.pdf', angles) shape = (64, 64) aspect = shape[0]/float(shape[1]) angle = -90 angleRange = 5 aspectRange = 0.5 filtered = pos_labels filtered = filter(lambda l: abs(l.ry*180.0/np.pi - angle) < angleRange/2.0, filtered)