From 1e7e12b3d1c859a310a58b79ecbd5eb40d68a4f3 Mon Sep 17 00:00:00 2001
From: Mohammad Khaleeliyeh <mohammad.khaleeliyeh@asinco.de>
Date: Fri, 9 Jun 2023 18:28:58 +0200
Subject: [PATCH] Code modified
---
filter_images_V5.py | 2 +-
filter_pipeline.py | 23 ++++++---
filters.py | 114 ++++++++++++++++++++++++++++++++++++++++++--
3 files changed, 128 insertions(+), 11 deletions(-)
diff --git a/filter_images_V5.py b/filter_images_V5.py
index 798d80d..b8f850f 100644
--- a/filter_images_V5.py
+++ b/filter_images_V5.py
@@ -5,7 +5,7 @@ import time
from datetime import datetime
import pandas as pd
-VIDEO = 'Videomaterial/WIN_20230414_13_41_55_Pro.mp4'
+VIDEO = 'Videomaterial/WIN_20230602_14_42_19_Pro.mp4'
capture = cv2.VideoCapture(VIDEO)
diff --git a/filter_pipeline.py b/filter_pipeline.py
index 1c22f6f..8dae246 100644
--- a/filter_pipeline.py
+++ b/filter_pipeline.py
@@ -4,10 +4,11 @@ import matplotlib.pyplot as plt
import time
from datetime import datetime
import pandas as pd
+import filters
-VIDEO = 'Videomaterial/WIN_20230414_13_41_55_Pro.mp4'
+VIDEO = 'Videomaterial/WIN_20230602_14_45_52_Pro.mp4'
capture = cv2.VideoCapture(VIDEO)
-capture.set(cv2.CAP_PROP_POS_FRAMES, 30 * 40) # skip 40 seconds
+capture.set(cv2.CAP_PROP_POS_FRAMES, 30 * 0) # skip 40 seconds
last = None
frame = None
@@ -34,23 +35,29 @@ def overlay_imgs(base, top):
return cv2.add(img1_bg, img2_fg)
+
def nothing_cb(val):
pass
# To control the Size of the Disply
-cv2.namedWindow(window, cv2.WINDOW_AUTOSIZE)
-cv2.createTrackbar('Canny_Min', window, 50, 255, nothing_cb)
-cv2.createTrackbar('Canny_Max', window, 100, 255, nothing_cb)
+cv2.namedWindow(window, cv2.WINDOW_NORMAL)
+cv2.createTrackbar('Canny_Min', window, 90, 255, nothing_cb)
+cv2.createTrackbar('Canny_Max', window, 150, 255, nothing_cb)
cv2.createTrackbar('Diff_Mix', window, 40, 100, nothing_cb)
+cv2.createTrackbar('HSV_Min', window, 40, 255, nothing_cb)
+cv2.createTrackbar('HSV_Max', window, 100, 255, nothing_cb)
+
-import filters
pipeline = [
('Original', filters.none),
+ #('GreenChannel', filters.greenfilter),
('Gray scale', filters.grayscale),
('Contrast and Blur', filters.medianBlur),
('Video Diff Multiple', filters.video_absdiff2),
+ ('Green filter abs', filters.green_absfilter),
('Canny edge detection', filters.filter_canny),
('Morph close', filters.filter_close),
+ ('gitter_filter', filters.gitter),
#('Morph open', filters.filter_open),
('Point extraction', filters.points_extract),
('Polyfit lines', filters.points_overlay)
@@ -59,7 +66,7 @@ pipeline = [
state = {} # Empty dictionary to store filters state
info = {
- 'abs_diff': 3, # 3 images for difference,
+ 'abs_diff': 2, # 3 images for difference,
'dim': (1920, 1080), #
'params': {}
}
@@ -76,6 +83,8 @@ while capture.isOpened():
info['params']['mix'] = cv2.getTrackbarPos('Diff_Mix', window) / 100.0
info['params']['canny_min'] = cv2.getTrackbarPos('Canny_Min', window)
info['params']['canny_max'] = cv2.getTrackbarPos('Canny_Max', window)
+ info['params']['hsv_min'] = cv2.getTrackbarPos('HSV_Min', window)
+ info['params']['hsv_max'] = cv2.getTrackbarPos('HSV_Max', window)
result = frame
for i, (name, filter) in enumerate(pipeline):
diff --git a/filters.py b/filters.py
index 35e4929..d743771 100644
--- a/filters.py
+++ b/filters.py
@@ -1,13 +1,110 @@
import cv2 as cv
import numpy as np
import pandas as pd
-
+import matplotlib.pyplot as plt
from collections import deque
def none(info, image, state):
+ if 'bufferOrginal' not in state:
+ state['bufferOrginal'] = deque(maxlen=info['abs_diff'])
+
+ bufferOrginal = state['bufferOrginal']
+ bufferOrginal.append(image)
+
+ return image, False
+def plot_points(x, y, px, py):
+ fig = plt.figure()
+ ax = fig.add_subplot()
+ ax.scatter(px, py, c='r')
+ ax.plot(x, y)
+ ax.set_xlim([0, 1280])
+ ax.set_ylim([720, 0])
+ plt.show()
+
+def gitter(info, image, state):
+ list_of_lines = []
+ # image Range ((1280, 720))
+ fig = plt.figure()
+ ax = fig.add_subplot()
+ ax.set_xlim([0, 1280])
+ ax.set_ylim([720, 0])
+
+ ax.grid(True, which='major')
+ diff_x = 50
+ diff_y = 50
+ treshold = 50
+
+ ax.set_xticks(range(0,1280, diff_x))
+ ax.set_yticks(range(0,720, diff_y))
+
+ for x in range(0,1280,diff_x):
+ for y in range(0,720,diff_y):
+ subimg = image[y:y+diff_y,x:x+diff_x]
+ indices = np.where(subimg > 0)
+ if (indices[1].size > treshold):
+ x_so = indices[1] + x
+ y_so = indices[0] + y
+
+ list_xy = np.column_stack((x_so, y_so)).astype(np.int32)
+ poly_xy = polyfit2(list_xy, x, x + diff_x, y, y + diff_y)
+ list_of_lines.append(poly_xy)
+
+ ax.scatter(x_so, y_so, c='r')
+ ax.plot(poly_xy[:,0], poly_xy[:,1], 'b')
+
+ #fig.show()
+
+ #plot_points(poly_xy[:,0], poly_xy[:,1], x_so, y_so)
+
+ plt.show()
return image, False
+# Cut green kanal
+def greenfilter(info, image, state):
+ # Umwandeln des Bildes in den Farbraum HSV
+ hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
+ # Definition des grünen Farbbereichs in HSV
+ lower_green = np.array([40, 10, 10])
+ upper_green = np.array([80, 240, 240])
+ # Erstellen einer Maske, die den grünen Farbbereich ausschließt
+ mask = cv.inRange(hsv, lower_green, upper_green)
+ # Invertieren der Maske, um den grünen Farbbereich auszuschließen
+ inverted_mask = cv.bitwise_not(mask)
+ # Anwenden der Maske auf das Bild
+ res = cv.bitwise_and(image, image, mask=inverted_mask)
+ return res,False
+
+def greenfilter_mask(image, info):
+ min_threshold = info['params']['hsv_min']
+ max_threshold = info['params']['hsv_max']
+
+ # Umwandeln des Bildes in den Farbraum HSV
+ hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
+ # Definition des grünen Farbbereichs in HSV
+ lower_green = np.array([min_threshold, 10, 10])
+ upper_green = np.array([max_threshold, 240, 240])
+ # Erstellen einer Maske, die den grünen Farbbereich ausschließt
+ mask = cv.inRange(hsv, lower_green, upper_green)
+ return mask
+
+def green_absfilter(info, image, state):
+ bufferOrginal = state['bufferOrginal']
+
+ res = None
+ for img in bufferOrginal:
+ mask = greenfilter_mask(img, info)
+ if res is None:
+ res = mask
+ else:
+ res = cv.bitwise_or(res, mask)
+
+ res_inv = cv.bitwise_not(res)
+ res_img = cv.bitwise_and(image, image, mask=res_inv)
+ return res_img,False
+
+
+
# Resize image to 1280x720 pixels
def resize(info, image, state):
res = cv.resize(image, (1280, 720))
@@ -64,11 +161,22 @@ def find_points(image):
return n_list
return None
+
+def polyfit2(n_list, xs, xe, ys, ye):
+ if n_list is not None:
+ p = np.polyfit(n_list[:,0], n_list[:,1], 1)
+ x = np.arange(xs, xe, 1)
+ y = np.polyval(p,x)
+ points = np.column_stack((x, y)).astype(np.int32)
+ points = points[(y >= ys) & (y <= ye)]
+
+ return points
+ return None
-def polyfit(n_list):
+def polyfit(n_list,n=4):
if n_list is not None:
- p = np.polyfit(n_list[:,0], n_list[:,1], 6)
+ p = np.polyfit(n_list[:,0], n_list[:,1], n)
x = np.arange(n_list[:,0][0], n_list[:,0][-1], 1)
y = np.polyval(p,x)
points = np.column_stack((x, y)).astype(np.int32)
--
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