Tweaks for convenience

00-find-corners.py

@@ -12,6 +12,7 @@ Usage:
 
 '''
 
+
 from pathlib import Path
 import numpy as np
 import cv2
@@ -19,13 +20,21 @@ import json
 import tqdm
 import math
 
-dataset = Path('hof3-cam-baumer')
-
+# SETTINGS:
+CALIB_FISHEYE = True
 # set needed detections. Use math.inf to scan the whole video
 needed_detections = math.inf # 20
-
 # Defining the dimensions of checkerboard
 CHECKERBOARD = (6,9)
+CROPPED_HEIGHT = None # 1520
+
+dataset = Path('hof3-cam-baumer-cropped')
+videofile = dataset / "chessboard.mp4"
+
+# -----
+# END OF SETTINGS
+
+snapshot_file = videofile.with_name(videofile.stem + '_snapshot.png')
 
 # termination criteria
 criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
@@ -39,7 +48,6 @@ objp[:,:2] = np.mgrid[0:CHECKERBOARD[0],0:CHECKERBOARD[1]].T.reshape(-1,2)
 objpoints = [] # 3d point in real world space
 imgpoints = [] # 2d points in image plane.
 
-videofile = dataset / "chessboard7.mp4"
 cap = cv2.VideoCapture(videofile)
 
 frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
@@ -56,11 +64,17 @@ p2 = tqdm.tqdm(total=needed_detections)
 first_found=False
 no_frames_for = 0
 
+needs_snapshot = not snapshot_file.exists()
+
 while ((found < needed_detections) if math.isfinite(needed_detections) else True):
     ret, img = cap.read() # Capture frame-by-frame
     if not ret:
         break
 
+    if needs_snapshot:
+        cv2.imwrite(snapshot_file, img)
+        needs_snapshot = False
+
     p.update()
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
@@ -98,5 +112,5 @@ cv2.destroyAllWindows()
 print(f"Found {found} detections")
 
 
-np.savez(dataset / "chessboard7-points.npz", objpoints=objpoints, imgpoints=imgpoints)
+np.savez(videofile.with_name(videofile.stem+'-points.npz') , objpoints=objpoints, imgpoints=imgpoints)
 

01-calibrate.py

@@ -20,18 +20,21 @@ import json
 import tqdm
 import math
 
+# SETTINGS:
 CALIB_FISHEYE = True
-
-dataset = Path('hof3-cam-baumer')
-
 # set needed detections. Use math.inf to scan the whole video
 needed_detections = math.inf # 20
-
 # Defining the dimensions of checkerboard
 CHECKERBOARD = (6,9)
+CROPPED_HEIGHT = None # 1520
 
-CROPPED_HEIGHT = 1520
+dataset = Path('hof3-cam-baumer-cropped')
+videofile = dataset / "chessboard.mp4"
 
+# -----
+# END OF SETTINGS
+
+snapshot_file = videofile.with_name(videofile.stem + '_snapshot.png')
 
 # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
 if not CALIB_FISHEYE:
@@ -46,7 +49,7 @@ else:
 objpoints = [] # 3d point in real world space
 imgpoints = [] # 2d points in image plane.
 
-videofile = dataset / "chessboard7.mp4"
+
 cap = cv2.VideoCapture(videofile)
 _, img = cap.read()
 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
@@ -60,7 +63,7 @@ dim = {
 }
 
 
-loaded = np.load(dataset / "chessboard-points.npz")
+loaded = np.load(videofile.with_name(videofile.stem+'-points.npz')  )
 objpoints, imgpoints = loaded['objpoints'], loaded['imgpoints']
 
 print(f"Calculating matrixes with {len(objpoints)} detections")
@@ -120,8 +123,12 @@ else:
     if not dim2:
         dim2 = dim1
     if not dim3:
-        dim3 = dim1
+        if CROPPED_HEIGHT:
             dim3 = (dim1[0], CROPPED_HEIGHT)
+        else:
+            dim3 = dim1
+
+
     scaled_K = K * dim1[0] / DIM[0]  # The values of K is to scale with image dimension.
     scaled_K[2][2] = 1.0  # Except that K[2][2] is always 1.0
         # This is how scaled_K, dim2 and balance are used to determine the final K used to un-distort image. OpenCV document failed to make this clear!
@@ -172,5 +179,7 @@ else:
     # img2 = cv2.imread("2.png")
     # cv2.imshow("none undistorted", img2)
     cv2.waitKey(0)
+    # while cv2.waitKey(0) != ord('q'):
+    #     pass
     cv2.destroyAllWindows()
 

02-testcalibration-and-draw-points.py

@@ -9,6 +9,7 @@ used for the homography later.
     this allows for more precise point placement, but might need some conversion in the next step
 3. Points are read and saved from points.json in the dataset folder
 """
+from pathlib import Path
 import cv2
 import json
 import os
@@ -16,11 +17,19 @@ import numpy as np
 
 from load_calibration import load_calibration
 
-dataset = 'hof3-cam-baumer'
-snapshot_img = 'snapshot.png'
-points_fname = dataset + '/points.json'
+# SETTINGS
+
+dataset = Path('hof3-cam-baumer-cropped')
+videofile = dataset / 'chessboard.mp4'
+points_fname = dataset / 'points.json'
+
+# END SETTINGS
+
+w, h, undistorted_img, undistort_points = load_calibration(dataset / "calibration.json")
+
+
+snapshot_file = videofile.with_name(videofile.stem + '_snapshot.png')
 
-w, h, undistorted_img, undistort_points = load_calibration(dataset + "/fisheye_calibration_data.json")
 # with open(dataset + '/calibration-chessboard4.json', 'r') as fp:
 # with open(dataset + '/calibration-chessboard4.json', 'r') as fp:
 
@@ -36,7 +45,7 @@ def add_point(event,x,y,flags,param):
         selected = None
         for i, p in enumerate(points):
             d = (p[0]-x)**2 + (p[1]-y)**2
-            if d < 14:
+            if d < 25:
                 selected = i
                 break
         print('click', selected)
@@ -52,7 +61,7 @@ cv2.namedWindow('original image')
 cv2.setMouseCallback('original image',add_point)
 
 # cap = cv2.VideoCapture("./hof2-hikvision.mp4")
-cap = cv2.VideoCapture(dataset + "/" + snapshot_img)
+cap = cv2.VideoCapture(snapshot_file)
 img_w = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
 img_h = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)