Merge branch 'main' of https://arnweb.nl/gitea/arne/EV5_Beeldherk_Bomen
This commit is contained in:
commit
4331f3b090
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@ -3,14 +3,11 @@ Script to extract 10cm x 10cm images from the template
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Accounts for (minor) rotation.
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command:
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python template.py input_folder output_folder
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volgorde maakt uit! heb niet die fancy library gebruikt
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python template.py input_directory
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known bugs:
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- plaatjes worden soms de verkeerde kant op gedraaid, ze staan wel recht
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maar 90 graden gedraaid
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- plaatjes zijn niet persé exact 10x10 cm als perspectief niet precies goed is
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- gekke crash bij herextractie van datapunten, zie todo
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Auteurs:
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Tom Selier
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@ -24,7 +21,7 @@ import os
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## Parameters ##
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# [%] Schaal output in percentages
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SCHAAL = 25
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SCHAAL = 100
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# [mm] 120 op calib a4, 180 op template
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@ -38,13 +35,13 @@ OFFSET = 20
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# Toon plaatjes (forceert pauze)
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PLAATJES = True
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PLAATJES = False
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# Wacht na elke plaatje op toets
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PAUZE = False
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# Sla plaatjes op
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SAVE = False
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SAVE = True
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# extra info
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VERBOSE = True
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@ -82,139 +79,167 @@ def findMin(array, index):
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min_val = element[index]
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return min_val
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input_folder = sys.argv[1]
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output_folder = sys.argv[2]
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input_directory = sys.argv[1]
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if(not os.path.isdir(input_folder)):
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print("Input folder not found")
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if(not os.path.isdir(input_directory)):
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print(input_directory)
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print("Input directory not found")
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exit()
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if(not os.path.isdir(output_folder)):
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print("Output folder not found")
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exit()
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### ARUCO PARAMETERS ###
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detector_params = cv2.aruco.DetectorParameters()
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detector_params.adaptiveThreshWinSizeMax = 150 # Takes longer, but better chance of finding markers
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dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_ARUCO_ORIGINAL)
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detector = cv2.aruco.ArucoDetector(dictionary, detector_params)
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### IMAGE CONVERSIE ###
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for file in os.listdir(input_folder):
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## Laad plaatjes in kleur ##
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filename = input_folder + '/' + file
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out_filename = output_folder + '/' + file
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img = cv2.imread(filename, 1)
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if VERBOSE:
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print(file)
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for folder in os.listdir(input_directory):
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if folder.endswith('.py'):
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print("Skipping", folder)
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continue
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## Herschaal de fotos ##
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(h, w) = img.shape[:2]
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x_scale = int(w/100*SCHAAL)
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y_scale = int(h/100*SCHAAL)
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small_img = cv2.resize(img, (x_scale, y_scale))
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(h_small, w_small) = small_img.shape[:2]
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if VERBOSE:
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print("Van %dx%dpx naar %dx%dpx geschaald"%(h,w,h_small,w_small))
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## Detecteer aruco markers ##
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(corners, ids, rejected) = detector.detectMarkers(small_img)
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new_image = cv2.aruco.drawDetectedMarkers(
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small_img,
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corners,
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ids)
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assert len(ids) == 4, "Not enough markers found in " + str(file)
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if VERBOSE:
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print("%d markers gedetecteerd" %len(ids))
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if folder.endswith('.jpg'):
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continue
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## Zoek de 'binnenste' hoekjes ##
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i = 0
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x = np.zeros(4, dtype=np.int32)
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y = np.zeros(4, dtype=np.int32)
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for corner in corners:
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x[i] = corner[0][getCorner(ids[i])][0]
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y[i] = corner[0][getCorner(ids[i])][1]
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cv2.circle(
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new_image,
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(x[i], y[i]),
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radius=3,
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color=(0, 254, 254),
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thickness=-1)
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i += 1
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if VERBOSE:
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print("Gedecteerde hoekjes (recht): ")
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print("\t x: ", end='')
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print(x)
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print("\t y: ", end='')
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print(y)
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## Draai de plaatjes recht ##
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x0 = x[np.where(ids == 0)[0][0]]
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x1 = x[np.where(ids == 1)[0][0]]
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x_dif = x0-x1
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y0 = y[np.where(ids == 0)[0][0]]
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y1 = y[np.where(ids == 1)[0][0]]
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y_dif = y0 - y1
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angle_rad = np.arctan(y_dif/x_dif)
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angle_deg = angle_rad * 180.0 / np.pi
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if(VERBOSE):
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print("%d graden gedraaid"%angle_deg)
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(cX, cY) = (w_small // 2, h_small // 2)
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matrix = cv2.getRotationMatrix2D((cX, cY), angle_deg, 1.0)
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warp_img = cv2.warpAffine(new_image, matrix, (w_small, h_small))
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## Herdetecteer de binnenste hoekjes op de gedraaide plaatjes ##
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mask = cv2.inRange(warp_img, (0, 253, 253), (0, 255, 255))
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warped_corners = []
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for i in range(4):
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coordinate = cv2.minMaxLoc(mask)[3]
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warped_corners.append(coordinate)
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cv2.circle(mask, warped_corners[i], 10, (0, 0, 0), -1)
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if VERBOSE:
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print("Gedecteerde hoekjes (gedraaid): ")
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print("\t", warped_corners)
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## Teken rode balken voor controle ##
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# feature voor ooit, nogal lastig
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## Calibratie van afstand met betrekking tot pixels ##
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xs = [corner[0] for corner in warped_corners]
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ys = [corner[1] for corner in warped_corners]
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x_max = np.amax(xs)
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x_min = np.amin(xs)
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x_diff = x_max - x_min
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calib_scale = x_diff / CALIB_AFSTAND
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if VERBOSE:
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print("Berekende schaal: %d pixels/mm"%calib_scale)
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## Crop de plaatjes ##
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top_left_x = findMin(warped_corners, 0)
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top_left_y = findMin(warped_corners, 1)
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bot_right_x = findMax(warped_corners, 0)
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bot_right_y = findMax(warped_corners, 1)
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offset = int((OFFSET+CORRECTIE)*calib_scale)
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crop_img = warp_img[
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top_left_y+offset:bot_right_y-offset,
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top_left_x+offset:bot_right_x-offset]
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## Check voor rode balken ##
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# zie boven
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## Output ##
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if PLAATJES:
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cv2.imshow('window', warp_img)
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cv2.imshow('cropped', crop_img)
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if SAVE:
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cv2.imwrite(out_filename, crop_img)
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if PAUZE or PLAATJES:
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cv2.waitKey(0)
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if VERBOSE:
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print("=============================================")
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path = os.path.join(input_directory, folder)
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if (path).endswith("_out"):
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continue
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out_folder = path + "_out"
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if (os.path.exists(out_folder) == False):
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if VERBOSE:
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print("Created folder: " + out_folder)
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os.mkdir(out_folder)
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for file in os.listdir(os.path.join(input_directory, folder)):
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## Laad plaatjes in kleur ##
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filename = input_directory + '/' + folder + '/' + file
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img = cv2.imread(filename, 1)
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assert img is not None, "Image path is wrong " + filename
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if VERBOSE:
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print(file)
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## Herschaal de fotos ##
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(h, w) = img.shape[:2]
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x_scale = int(w/100*SCHAAL)
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y_scale = int(h/100*SCHAAL)
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if SCHAAL != 100:
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small_img = cv2.resize(img, (x_scale, y_scale))
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else:
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small_img = img
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(h_small, w_small) = small_img.shape[:2]
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if VERBOSE:
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print("Van %dx%dpx naar %dx%dpx geschaald"%(h,w,h_small,w_small))
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## Detecteer aruco markers ##
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(corners, ids, rejected) = detector.detectMarkers(small_img)
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new_image = cv2.aruco.drawDetectedMarkers(
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small_img,
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corners,
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ids)
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if ids is None:
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print("Skipping: ", filename)
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print("=============================================")
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continue
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if len(ids) != 4:
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print("Skipping: ", filename)
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print("=============================================")
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continue
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if VERBOSE:
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print("%d markers gedetecteerd" %len(ids))
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## Zoek de 'binnenste' hoekjes ##
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i = 0
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x = np.zeros(4, dtype=np.int32)
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y = np.zeros(4, dtype=np.int32)
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for corner in corners:
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x[i] = corner[0][getCorner(ids[i])][0]
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y[i] = corner[0][getCorner(ids[i])][1]
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cv2.circle(
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new_image,
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(x[i], y[i]),
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radius=5,
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color=(0, 254, 254),
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thickness=-1)
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i += 1
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if VERBOSE:
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print("Gedecteerde hoekjes (recht): ")
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print("\t x: ", end='')
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print(x)
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print("\t y: ", end='')
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print(y)
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## Draai de plaatjes recht ##
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x0 = x[np.where(ids == 0)[0][0]]
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x1 = x[np.where(ids == 1)[0][0]] # TODO: Fix whatevers happening here
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x_dif = x0-x1
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y0 = y[np.where(ids == 0)[0][0]]
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y1 = y[np.where(ids == 1)[0][0]]
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y_dif = y0 - y1
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angle_rad = np.arctan(y_dif/x_dif)
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angle_deg = angle_rad * 180.0 / np.pi
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if(VERBOSE):
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print("%d graden gedraaid"%angle_deg)
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(cX, cY) = (w_small // 2, h_small // 2)
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matrix = cv2.getRotationMatrix2D((cX, cY), angle_deg, 1.0)
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warp_img = cv2.warpAffine(new_image, matrix, (w_small, h_small))
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## Herdetecteer de binnenste hoekjes op de gedraaide plaatjes ##
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mask = cv2.inRange(warp_img, (0, 253, 253), (0, 255, 255))
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warped_corners = []
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for i in range(4):
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coordinate = cv2.minMaxLoc(mask)[3]
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warped_corners.append(coordinate)
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cv2.circle(mask, warped_corners[i], 10, (0, 0, 0), -1)
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if VERBOSE:
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print("Gedecteerde hoekjes (gedraaid): ")
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print("\t", warped_corners)
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## Teken rode balken voor controle ##
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# feature voor ooit, nogal lastig
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## Calibratie van afstand met betrekking tot pixels ##
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xs = [corner[0] for corner in warped_corners]
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ys = [corner[1] for corner in warped_corners]
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x_max = np.amax(xs)
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x_min = np.amin(xs)
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x_diff = x_max - x_min
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calib_scale = x_diff / CALIB_AFSTAND
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if VERBOSE:
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print("Berekende schaal: %d pixels/mm"%calib_scale)
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## Crop de plaatjes ##
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top_left_x = findMin(warped_corners, 0)
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top_left_y = findMin(warped_corners, 1)
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bot_right_x = findMax(warped_corners, 0)
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bot_right_y = findMax(warped_corners, 1)
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offset = int((OFFSET+CORRECTIE)*calib_scale)
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crop_img = warp_img[
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top_left_y+offset:bot_right_y-offset,
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top_left_x+offset:bot_right_x-offset]
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## Check voor rode balken ##
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# zie boven
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## Output ##
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if PLAATJES:
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cv2.imshow('window', warp_img)
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cv2.imshow('cropped', crop_img)
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if SAVE:
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out_path = out_folder + "/" + file
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print("Saving to:", out_path)
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cv2.imwrite(out_path, crop_img)
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if PAUZE or PLAATJES:
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cv2.waitKey(0)
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if VERBOSE:
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print("=============================================")
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cv2.destroyAllWindows()
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@ -202,7 +202,7 @@ class MainApp:
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self.axs[column, row].title.set_text(
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"mean: %c:%d %c:%d %c:%d \n std: %c:%d %c:%d %c:%d"
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%(labels[0], mean[0], labels[1], mean[1], labels[2], mean[2],
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labels[0], std[0], labels[1], std[1], labels[2], std[2]))
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labels[0], std[0], labels[1], std[1], labels[2], std[2]))
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def update(self, event=None):
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path = self.img_path.get()
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@ -262,6 +262,7 @@ class MainApp:
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# Canny edge
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img_canny = cv2.Canny(image=img_blur,threshold1=ct1,threshold2=ct2)
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self.add_output(img_canny, "Canny Edge")
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self.writeStats(img, ('B', 'G', 'R'), 0, 0)
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# BGR
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self.add_output(img[:, :, 0], "BGR B")
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@ -270,7 +271,6 @@ class MainApp:
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if img is not None:
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self.drawHist(img, ('B', 'G', 'R'), 0, 0)
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self.writeStats(img, ('B', 'G', 'R'), 0, 0)
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# HSV
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img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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