Video comparison script

python-api/tests/scripts/cv.py

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+import os
+import cv2
+import sys
+
+from scipy.misc import imread
+from scipy.linalg import norm
+from scipy import sum, average
+
+import subprocess
+
+def check_video(video, cmp_folder):
+
+
+    generate_keyframes(video, cmp_folder)
+
+    result = {}
+    for x in os.listdir('reference_frames'):
+        try:
+            res = comp_image('reference_frames/'+x, 'test_frames/'+x)
+            # if res:
+            result[x] = res
+        except Exception as e:
+            pass
+    for x in result:
+        print x, result[x]
+
+
+def generate_keyframes(video, cmp_folder):
+    cmd = "/usr/local/bin/ffmpeg -i {0} -f image2 -vf fps=fps=1 {1}/foo-%d.png".format(video, cmp_folder)
+    # print cmd
+    with open(os.devnull, 'w') as tempf:
+            proc = subprocess.Popen(
+            cmd.split(),
+            stdout=tempf,
+            stderr=tempf,
+            bufsize=-1,
+            shell=False)
+            proc.wait()
+
+
+def to_grayscale(arr):
+    "If arr is a color image (3D array), convert it to grayscale (2D array)."
+    if len(arr.shape) == 3:
+        return average(arr, -1)  # average over the last axis (color channels)
+    else:
+        return arr
+
+def comp_image(image1, image2):
+    file1, file2 = (image1, image2)
+    # read images as 2D arrays (convert to grayscale for simplicity)
+    img1 = imread(file1).astype(float)
+    img2 = imread(file2).astype(float)
+    # compare
+    n_0 = compare_images(img1, img2)
+    return n_0*1.0/img1.size
+    # print "Manhattan norm:", n_m, "/ per pixel:", n_m/img1.size
+    # print "Zero norm:", n_0, "/ per pixel:", n_0*1.0/img1.size
+
+def normalize(arr):
+    rng = arr.max()-arr.min() + 1e-10
+    amin = arr.min()
+    return (arr-amin)*255/rng
+
+
+def compare_images(img1, img2):
+    # normalize to compensate for exposure difference, this may be unnecessary
+    # consider disabling it
+    img1 = normalize(img1)
+    img2 = normalize(img2)
+    # calculate the difference and its norms
+    diff = img1 - img2  # elementwise for scipy arrays
+    # m_norm = sum(abs(diff))  # Manhattan norm
+    z_norm = norm(diff.ravel(), 0)  # Zero norm
+    return z_norm
+
+def main():
+    video1 = 'rec1.data'
+    video = 'rec2.data'
+    generate_keyframes(video1, 'reference_frames')
+    print check_video(video, 'test_frames')
+
+main()
+