init

capture.py

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+import cv2
+import time
+import pandas
+from datetime import datetime
+
+prev_frame = None
+times = []
+# df = pandas.DataFrame(columns=["start", "end"])
+video = cv2.VideoCapture(0)
+status_new = 0
+counter = 0
+low_red = (176, 132, 97)
+high_red = (209, 151, 114)
+face_cascade = cv2.CascadeClassifier("smile.xml")
+
+while True:
+    status_new, status_old = 0, status_new
+    check, frame = video.read()
+    only_cat = cv2.inRange(frame, low_red, high_red)
+    # cat_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    gray = cv2.GaussianBlur(gray, (21, 21), 0)
+
+    if prev_frame is None:
+        prev_frame = gray
+        # continue
+
+
+    delta_frame = cv2.absdiff(prev_frame, gray)
+    prev_frame = gray
+    thresh_delta = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
+    thresh_frame = cv2.dilate(thresh_delta, None, iterations=2)
+
+    (_,cnts,_) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    print(len(cnts))
+    for contour in cnts:
+        if cv2.contourArea(contour) < 1000:
+            continue
+        status_new, status_old = 1, status_new
+
+        (x, y, w, h) = cv2.boundingRect(contour)
+        # cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 3)
+    # status_list.append(status)
+    if status_new != status_old:
+        times.append(datetime.now())
+        cv2.imwrite('media/capture{}.png'.format(counter), frame)
+        counter += 1
+    # cv2.imshow("capt", gray)
+    # cv2.imshow("delta", delta_frame)
+    # cv2.imshow("threshold", thresh_frame)
+    faces = face_cascade.detectMultiScale(gray,
+                                          scaleFactor=1.1,
+                                          minNeighbors=10)
+    # for x, y, w, h in faces:
+    #     img = cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 3)
+    # print(type(faces))
+    # cv2.imshow("face_detector", img)
+    cv2.imshow('cat', only_cat)
+    cv2.imshow("rectangle", frame)
+    key = cv2.waitKey(1)
+    if key==ord('q'):
+        break
+# print(times)
+#
+# for t in range(0, len(times), 2):
+#     df = df.append({"start": times[t], "end": times[t+1]}, ignore_index=True)
+#
+# df.to_csv("times.csv")
+video.release()
+cv2.destroyAllWindows

face_detector.py

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+import cv2
+
+
+face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+img = cv2.imread("Screenshot from 2018-07-20 14-00-25.png")
+gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+faces = face_cascade.detectMultiScale(gray_img,
+                                      scaleFactor=1.05,
+                                      minNeighbors=5)
+for x, y, w, h in faces:
+    img = cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 3)
+# print(type(faces))
+cv2.imshow("face_detector", img)
+cv2.waitKey(0)
+cv2.destroyAllWindows()

make_gif.py

@@ -0,0 +1,10 @@
+import os
+import imageio
+
+path = "media/остап_спальня"
+file_names = os.listdir(path)
+file_names.sort()
+images = [imageio.imread(path+"/"+fn) for fn in file_names]
+
+
+imageio.mimsave('movie.gif', images, duration=0.2)

requirements.txt

@@ -0,0 +1,17 @@
+bokeh==0.13.0
+imageio==2.3.0
+images2gif==1.0.1
+Jinja2==2.10
+MarkupSafe==1.0
+numpy==1.14.5
+opencv-python==3.4.1.15
+packaging==17.1
+pandas==0.23.3
+Pillow==5.2.0
+pkg-resources==0.0.0
+pyparsing==2.2.0
+python-dateutil==2.7.3
+pytz==2018.5
+PyYAML==3.13
+six==1.11.0
+tornado==5.1

script1.py

@@ -0,0 +1,20 @@
+import cv2
+import os
+
+path = "media/Screenshot from 2018-07-18 11-41-15.png"
+img = cv2.imread(path, 0)
+
+print(type(img))
+img_path = "/home/anya/Изображения/"
+files = os.listdir(img_path)
+for i in files:
+    img = cv2.imread(img_path + i, 0)
+    re = cv2.resize(img, (100, 100))
+    cv2.imshow("Hey", re)
+    cv2.waitKey(500)
+    cv2.destroyAllWindows()
+    cv2.imwrite("media/resized_" + i, re)
+# print(list(files) )
+# cv2.imshow("fractal", img)
+# cv2.waitKey(0)
+# cv2.destroyAllWindows()

setup.py

@@ -0,0 +1,48 @@
+import cv2
+import numpy as np
+# import video
+
+if __name__ == '__main__':
+    def nothing(*arg):
+        pass
+
+cv2.namedWindow( "result" ) # создаем главное окно
+cv2.namedWindow( "settings" ) # создаем окно настроек
+
+cap = cv2.VideoCapture(0)
+# создаем 6 бегунков для настройки начального и конечного цвета фильтра
+cv2.createTrackbar('h1', 'settings', 0, 255, nothing)
+cv2.createTrackbar('s1', 'settings', 0, 255, nothing)
+cv2.createTrackbar('v1', 'settings', 0, 255, nothing)
+cv2.createTrackbar('h2', 'settings', 255, 255, nothing)
+cv2.createTrackbar('s2', 'settings', 255, 255, nothing)
+cv2.createTrackbar('v2', 'settings', 255, 255, nothing)
+crange = [0,0,0, 0,0,0]
+
+while True:
+    flag, img = cap.read()
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV )
+
+    # считываем значения бегунков
+    h1 = cv2.getTrackbarPos('h1', 'settings')
+    s1 = cv2.getTrackbarPos('s1', 'settings')
+    v1 = cv2.getTrackbarPos('v1', 'settings')
+    h2 = cv2.getTrackbarPos('h2', 'settings')
+    s2 = cv2.getTrackbarPos('s2', 'settings')
+    v2 = cv2.getTrackbarPos('v2', 'settings')
+
+    # формируем начальный и конечный цвет фильтра
+    h_min = np.array((h1, s1, v1), np.uint8)
+    h_max = np.array((h2, s2, v2), np.uint8)
+
+    # накладываем фильтр на кадр в модели HSV
+    thresh = cv2.inRange(hsv, h_min, h_max)
+
+    cv2.imshow('result', thresh)
+
+    ch = cv2.waitKey(5)
+    if ch == 27:
+        break
+
+cap.release()
+cv2.destroyAllWindows

times.csv

@@ -0,0 +1,18 @@
+,start,end
+0,2018-07-20 16:25:51.415964,2018-07-20 16:25:51.449240
+1,2018-07-20 16:25:51.487239,2018-07-20 16:25:51.517014
+2,2018-07-20 16:25:52.719849,2018-07-20 16:25:52.748115
+3,2018-07-20 16:25:52.784534,2018-07-20 16:25:52.818577
+4,2018-07-20 16:25:52.850347,2018-07-20 16:25:53.650743
+5,2018-07-20 16:25:53.682903,2018-07-20 16:25:53.713877
+6,2018-07-20 16:25:53.752210,2018-07-20 16:25:54.980915
+7,2018-07-20 16:25:55.015023,2018-07-20 16:25:55.054432
+8,2018-07-20 16:25:55.083007,2018-07-20 16:25:55.114010
+9,2018-07-20 16:25:55.151263,2018-07-20 16:25:55.681425
+10,2018-07-20 16:25:55.713382,2018-07-20 16:25:55.745624
+11,2018-07-20 16:25:55.782112,2018-07-20 16:25:56.982078
+12,2018-07-20 16:25:57.016760,2018-07-20 16:25:57.047928
+13,2018-07-20 16:25:57.078765,2018-07-20 16:25:57.113705
+14,2018-07-20 16:25:57.946889,2018-07-20 16:25:57.980079
+15,2018-07-20 16:25:58.017876,2018-07-20 16:25:58.048768
+16,2018-07-20 16:25:58.079373,2018-07-20 16:25:58.115729