def test_generate_points_from_line_90_degrees_passing_through_5_0(self): line = LineModel(1, 0, -5) x1 = 20 x2 = 40 y1 = 10 y2 = 30 new_points = LineModel.generate_points_from_line(line, x1, y1, x2, y2) for p in new_points: print("Testing point=%s" % (p)) self.assertTrue(p.Y >= y1) self.assertTrue(p.Y <= y2)
def test_generate_points_from_line_45_degrees_passing_through_0_0(self): line = LineModel(-1, 1, 0) x1 = 20 x2 = 40 y1 = 10 y2 = 30 new_points = LineModel.generate_points_from_line(line, x1, y1, x2, y2) for p in new_points: print("Testing point=%s" % (p)) self.assertTrue(p.X >= x1) self.assertTrue(p.X <= x2)
def test_run_with_very_simple_image(self): # #get a list of points # folder_script=os.path.dirname(__file__) filename_input="Line_50x30.png" file_noisy_line=os.path.join(folder_script,"./data/",filename_input) np_image=skimage.io.imread(file_noisy_line,as_gray=True) lst_points=Util.create_points_from_numpyimage(np_image) # #initialize RansalHelper # helper1=RansacLineHelper() helper1.add_points(lst_points) helper1.max_iterations=1000 #10000 did not work helper1.min_points_for_model=2 helper1.threshold_error=3 #10 helper1.threshold_inlier_count=3 result_model=helper1.run() print("RANSAC-complete") print("Found model %s , polar=%s" % (result_model,result_model.display_polar())) # #Superimpose the new line over the image # folder_results=os.path.join(folder_script,"../out/") count_of_files=len(os.listdir(folder_results)) filename_results=("Line_50x30.%d.png" % (count_of_files) ) file_result=os.path.join(folder_results,filename_results) x_lower=0 x_upper=np_image.shape[1]-1 y_lower=0 y_upper=np_image.shape[0]-1 new_points=LineModel.generate_points_from_line(result_model,x_lower,y_lower,x_upper,y_upper) np_superimposed=Util.superimpose_points_on_image(np_image,new_points,100,255,100) skimage.io.imsave(file_result,np_superimposed) # #Asserts! # x_intercept=result_model.xintercept() y_intercept=result_model.yintercept() self.assertTrue ( x_intercept > 30,"X intercept below threshold") self.assertTrue ( x_intercept < 50,"X intercept above threshold") self.assertTrue ( y_intercept > 30,"Y intercept above threshold") self.assertTrue ( y_intercept < 45,"Y intercept below threshold") self.assertTrue(len(result_model.points),5) for pt in result_model.points: distance_from_line=result_model.compute_distance(pt) self.assertTrue(distance_from_line <= helper1.threshold_error)
def run_ransac(filename): folder_script = os.path.dirname(__file__) #Images which did not generate good results: # NoisyImage_3.png # NoisyLine-Gaussian-sp-0.80.111.png file_noisy_line = os.path.join(folder_script, "./input/", filename) np_image = skimage.io.imread(file_noisy_line, as_gray=True) # #Iterate over all cells of the NUMPY array and convert to array of Point classes # lst_all_points = Util.create_points_from_numpyimage(np_image) # #begin RANSAC # ransac_maxiterations = 12000 #12000 #6000 #12000 worked well ransac_minpoints = 5 #5 worked well #2 gave very bad results #20 worked well ransac_threshold = 5 #25 worked well for 'NoisyLine-Gaussian-sp-0.80.104.png' 15 and 5 did not #Nothing worked well for 'NoisyLine-Gaussian-sp-0.80.111.png" , tried increasing to 35 #3 for first set when points were much closer #5 produced too much deviation ransac_mininliers = 10 helper = RansacLineHelper() helper.max_iterations = ransac_maxiterations helper.min_points_for_model = ransac_minpoints helper.threshold_error = ransac_threshold helper.threshold_inlier_count = ransac_mininliers helper.add_points(lst_all_points) model = helper.run() #Display the model , you could render over the original picture print("-------------------------------------") print("RANSAC-complete") print("Found model %s , polar=%s" % (model, model.display_polar())) # #Generate an output image with the model line # filename_noextension = no_extension = os.path.splitext(filename)[0] now = datetime.datetime.now() filename_result = ("%s-%s.result.png") % ( filename_noextension, now.strftime("%Y-%m-%d-%H-%M-%S")) file_result = os.path.join(folder_script, "./out/", filename_result) #Load input image into array np_image_result = skimage.io.imread(file_noisy_line, as_gray=True) new_points = LineModel.generate_points_from_line( model, 0, 0, np_image_result.shape[1] - 1, np_image_result.shape[0] - 1) np_superimposed = Util.superimpose_points_on_image(np_image_result, new_points, 100, 255, 100) #Save new image skimage.io.imsave(file_result, np_superimposed)