astatin3/vid-to-3d
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Make this thing slightly more efficient

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Astatin3
2024-07-31 11:24:17 -06:00
parent 9b1b382486
commit 2e3969bec3
1 changed files with 9 additions and 8 deletions
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main.py
+9 -8
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@@ -13,9 +13,10 @@ def process_video(video_path, min_similarity, output_folder):
print("Error opening video file") print("Error opening video file")
return return
match_frame = None
prev_frame = None prev_frame = None
kp1, ds1 = None, None
i = 0 i = 0
while cap.isOpened(): while cap.isOpened():
@@ -28,23 +29,24 @@ def process_video(video_path, min_similarity, output_folder):
if prev_frame is None: if prev_frame is None:
prev_frame = frame prev_frame = frame
match_frame = frame kp1, des1 = orb.detectAndCompute(prev_frame, None)
cv2.imwrite(os.path.join(output_folder, os.path.basename(video_path)+"-"+str(i)+".png"), prev_frame)
print("Initial frame") print("Initial frame")
continue continue
cv2.imshow('Frame', frame) cv2.imshow('Frame', frame)
similarity = orb_similarity(match_frame, frame) similarity = orb_similarity(kp1, des1, frame)
print(f"Similarity: {similarity}, ", end='') print(f"Similarity: {similarity}, ", end='')
if similarity < min_similarity: if similarity < min_similarity:
match_frame = prev_frame kp1, des1 = orb.detectAndCompute(prev_frame, None)
if(not os.path.isdir(output_folder)): if(not os.path.isdir(output_folder)):
os.mkdir(output_folder) os.mkdir(output_folder)
cv2.imwrite(os.path.join(output_folder, os.path.basename(video_path)+"-"+str(i)+".png"), match_frame) cv2.imwrite(os.path.join(output_folder, os.path.basename(video_path)+"-"+str(i)+".png"), prev_frame)
print("Lost continuity, new match frame") print("Lost continuity, new match frame")
else: else:
print("Skipped!") print("Skipped!")
@@ -59,12 +61,11 @@ def process_video(video_path, min_similarity, output_folder):
orb = cv2.ORB_create() orb = cv2.ORB_create()
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
def orb_similarity(img1, img2): def orb_similarity(kp1, des1, img2):
kp1, des1 = orb.detectAndCompute(img1, None)
kp2, des2 = orb.detectAndCompute(img2, None) kp2, des2 = orb.detectAndCompute(img2, None)
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
matches = bf.match(des1, des2) matches = bf.match(des1, des2)
similarity = len(matches) / min(len(kp1), len(kp2)) similarity = len(matches) / min(len(kp1), len(kp2))