def test_readme_video_images(self):
# images from sequence in video
p = pipeline.Pipeline(1)
imgs = image_util.loadImagesRGB(IMG_DIR2)
for i, img in enumerate(imgs):
draw_img, labels, heatmap, boxed_image = p.process_verbose(
np.copy(img))
out = image_util.arrangeImages(
[img, boxed_image, heatmap, labels[0], draw_img],
["original", "car detections", "heatmap", "labels", "result"],
figsize=(5, 1))
image_util.saveImage(
out, TEST_OUT_DIR + "/readme_videoprocess" + str(i) + ".png")
p = pipeline.Pipeline(9)
imgs = image_util.loadImagesRGB(IMG_DIR2)
for i, img in enumerate(imgs):
draw_img, labels, heatmap, boxed_image = p.process_verbose(
np.copy(img))
out = image_util.arrangeImages(
[img, boxed_image, heatmap, labels[0], draw_img],
["original", "car detections", "heatmap", "labels", "result"],
figsize=(5, 1))
image_util.saveImage(
out, TEST_OUT_DIR + "/readme_videoprocess_with_history" +
str(i) + ".png")
def test_process(self):
p = pipeline.Pipeline()
imgs = image_util.loadImagesRGB(IMG_DIR)
for i, img in enumerate(imgs):
processed_img = p.process(img)
image_util.saveBeforeAfterImages(
img, "Original", processed_img, "Thresholded",
TEST_OUT_DIR + "/thresholded" + str(i) + ".jpg")
def test_03_undistortTestImages(self):
imgs = image_util.loadImagesRGB(TEST_IMAGES_DIR)
ret, mtx, dist, rvecs, tvecs = uut.cachedCalibrateCameraFromDir(
CAMERA_CAL_DIR)
for i, img in enumerate(imgs):
dimg = cv2.undistort(img, mtx, dist)
image_util.saveBeforeAfterImages(
img, "Original", dimg, "Undistorted",
TEST_OUT_DIR + "/test_" + str(i) + "_undistorted.png")
def _test_process(self):
p = pipeline.Pipeline(1)
imgs = image_util.loadImagesRGB(IMG_DIR)
for i, img in enumerate(imgs):
processed_img = p.process(np.copy(img))
out = image_util.arrangeImages([img, processed_img],
["original", "car detection"],
figsize=(4, 2))
image_util.saveImage(
out, TEST_OUT_DIR + "/identified_boxes" + str(i) + ".png")
def calibrateCameraFromDir(path):
objpoints = [] # 3d points in real world space
imgpoints = [] # 2d points in image plane.
imgs = image_util.loadImagesRGB(path)
for img in imgs:
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Find the chessboard corners
ret, corners = cv2.findChessboardCorners(gray, CHESS_BOARD_SHAPE, None)
# If found, add object points, image points
if ret == True:
objpoints.append(objp)
imgpoints.append(corners)
# Do camera calibration given object points and image points
img_size = (img.shape[1], img.shape[0])
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size,None,None)
return ret, mtx, dist, rvecs, tvecs
def test_sliding_windows_1(self) :
imgs = image_util.loadImagesRGB(IMG_FILE_DIR)
for img in imgs:
# search with box size 64 * 1 = 64
ystart = 380
ystop = 480
scale = 1.0
self.draw_sliding_windows(TEST_OUT_DIR+"windows_1.png", img, ystart, ystop, scale)
# search with box size 64 * 1.5 = 96
ystart = 400
ystop = 600
scale = 1.5
self.draw_sliding_windows(TEST_OUT_DIR+"windows_2.png",img, ystart, ystop, scale)
# search with box size 64 * 2.5 = 160
ystart = 500
ystop = 700
scale = 2.5
self.draw_sliding_windows(TEST_OUT_DIR+"windows_3.png", img, ystart, ystop, scale)
def test_03_createBeforeAfterImages(self):
imgs = uut.loadImagesRGB(CAMERA_CAL)
for i,img in enumerate(imgs):
uut.saveBeforeAfterImages(img, "before", img, "after", TEST_OUT_DIR+"/before_after_"+str(i)+".png")
def test_02_loadAndSave(self):
imgs = uut.loadImagesRGB(CAMERA_CAL)
for i,img in enumerate(imgs):
print("2" + str(img.shape))
uut.saveImage(img, TEST_OUT_DIR+"/out"+str(i)+".png")
def test_01_load(self):
imgs = uut.loadImagesRGB(CAMERA_CAL)
self.assertEqual(20,len(imgs))
for img in imgs:
print("1" + str(img.shape))