def ImagePro(self,capture,orig,processed,storage,grid,squares):
orig = cv.QueryFrame(capture)
#cv.Normalize(orig)
# filter for all yellow and blue - everything else is black
processed = processor.colorFilterCombine(orig, "yellow", "blue" ,s)
#robot = processor.colorFilterCombine(orig, "red", "green" ,s)
# Some processing and smoothing for easier circle detection
cv.Canny(processed, processed, 5, 70, 3)
cv.Smooth(processed, processed, cv.CV_GAUSSIAN, 7, 7)
#cv.Canny(robot, robot, 5, 70, 3)
#cv.Smooth(robot, robot, cv.CV_GAUSSIAN, 7, 7)
#cv.ShowImage('processed2', processed)
# Find&Draw circles
processor.find_circles(processed, storage, 100)
#processor.find_circles(robot, storage2, 100)
#if it is in the range of 1 to 9, we can try and recalibrate our filter
#if 1 <= storage.rows < 10:
# s = autocalibrate(orig, storage)
#print storage2
combined = processor.robot_tracking(orig, squares)
processor.draw_circles(storage, orig)
#processor.draw_circles(storage2, orig)
mask = cv.CreateImage((400,300), cv.IPL_DEPTH_8U, 3)
cv.Resize(orig,mask)
return mask
def ImagePro(self,capture,orig,processed,storage,grid,squares):
orig = cv.QueryFrame(capture)
#cv.Normalize(orig)
# filter for all yellow and blue - everything else is black
processed = processor.colorFilterCombine(orig, "yellow", "blue" ,s)
# Some processing and smoothing for easier circle detection
cv.Canny(processed, processed, 5, 70, 3)
cv.Smooth(processed, processed, cv.CV_GAUSSIAN, 7, 7)
#cv.ShowImage('processed2', processed)
# Find&Draw circles
processor.find_circles(processed, storage, 100)
#if it is in the range of 1 to 9, we can try and recalibrate our filter
#if 1 <= storage.rows < 10:
# s = autocalibrate(orig, storage)
combined = processor.robot_tracking(orig, squares)
processor.draw_circles(storage, orig)
#warp = processor.update_grid(storage, orig, grid)
# Delete and recreate the storage so it has the correct width
#del(storage)
#storage = cv.CreateMat(orig.width, 1, cv.CV_32FC3)
#cv.ShowImage('output', orig)
#return processed
#cv.ShowImage('grid', warp)
#warp = perspective_transform(orig)
#cv.ShowImage('warped', warp)
#combined = processor.robot_tracking(orig, squares)
mask = cv.CreateImage((400,300), cv.IPL_DEPTH_8U, 3)
cv.Resize(orig,mask)
return mask
def ImagePro(self, capture, orig, processed, storage, grid):
orig = cv.QueryFrame(capture)
#cv.Normalize(orig)
# filter for all yellow and blue - everything else is black
processed = processor.colorFilterCombine(orig, "yellow", "blue", s)
# Some processing and smoothing for easier circle detection
cv.Canny(processed, processed, 5, 70, 3)
cv.Smooth(processed, processed, cv.CV_GAUSSIAN, 7, 7)
#cv.ShowImage('processed2', processed)
# Find&Draw circles
processor.find_circles(processed, storage, 100)
#if it is in the range of 1 to 9, we can try and recalibrate our filter
#if 1 <= storage.rows < 10:
# s = autocalibrate(orig, storage)
processor.draw_circles(storage, orig)
#warp = processor.update_grid(storage, orig, grid)
# Delete and recreate the storage so it has the correct width
#del(storage)
#storage = cv.CreateMat(orig.width, 1, cv.CV_32FC3)
#cv.ShowImage('output', orig)
#return processed
#cv.ShowImage('grid', warp)
#warp = perspective_transform(orig)
#cv.ShowImage('warped', warp)
mask = cv.CreateImage((640, 480), cv.IPL_DEPTH_8U, 3)
cv.Resize(orig, mask)
return mask
