diff --git a/README.md b/README.md
index 8136387..41d37ab 100644
--- a/README.md
+++ b/README.md
@@ -14,9 +14,11 @@ it will capture screenshots of unique frames and save it output folder...once sc
# Example
There are two sample video avilable in "./input", you can test the code using these input by running
-python video2pdfslides.py "./input/Test Video 1.mp4" (4 unique slide)
-python video2pdfslides.py "./input/Test Video 2.mp4" (19 unique slide)
+python video2pdfslides.py "./input/Test Video 1.mp4" (4 unique slide)
+python video2pdfslides.py "./input/Test Video 2.mp4" (19 unique slide)
+## Running the code for on a folder of presentations.
+python video2pdfslides.py -r ./folder_path
# More
The default parameters works for a typical video presentation. But if the video presentation has lots of animations, the default parametrs won't give a good results, you may notice duplicate/missing slides. Don't worry, you can make it work for any video presentation, even the ones with animations, you just need to fine tune and figure out the right set of parametrs, The 3 most important parameters that I would recommend to get play around is "MIN_PERCENT", "MAX_PERCENT", "FGBG_HISTORY". The description of these variables can be found in code comments.
diff --git a/requirements.txt b/requirements.txt
index b2b581b..e7a1d7e 100755
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
imutils==0.5.4
-opencv_python==4.5.2.52
+opencv_python
img2pdf==0.4.1
diff --git a/video2pdfslides.py b/video2pdfslides.py
index 9daebc2..67c11c0 100644
--- a/video2pdfslides.py
+++ b/video2pdfslides.py
@@ -63,6 +63,8 @@ def detect_unique_screenshots(video_path, output_folder_screenshot_path):
# varThreshold = Threshold on the squared Mahalanobis distance between the pixel and the model to decide whether a pixel is well described by the background model. This parameter does not affect the background update.
# detectShadows = If true, the algorithm will detect shadows and mark them. It decreases the speed a bit, so if you do not need this feature, set the parameter to false.
+ # Initialize fgbg a Background object with Parameters
+ # ... (rest of the function remains unchanged)
fgbg = cv2.createBackgroundSubtractorMOG2(history=FGBG_HISTORY, varThreshold=VAR_THRESHOLD,detectShadows=DETECT_SHADOWS)
@@ -110,7 +112,13 @@ def detect_unique_screenshots(video_path, output_folder_screenshot_path):
def initialize_output_folder(video_path):
'''Clean the output folder if already exists'''
- output_folder_screenshot_path = f"{OUTPUT_SLIDES_DIR}/{video_path.rsplit('/')[-1].split('.')[0]}"
+ if os.path.isdir(video_path):
+ # Assuming the directory name is the base name for the output folder
+ base_name = os.path.basename(video_path)
+ else:
+ base_name = os.path.splitext(os.path.basename(video_path))[0]
+
+ output_folder_screenshot_path = f"{OUTPUT_SLIDES_DIR}/{base_name}"
if os.path.exists(output_folder_screenshot_path):
shutil.rmtree(output_folder_screenshot_path)
@@ -119,9 +127,10 @@ def initialize_output_folder(video_path):
print('initialized output folder', output_folder_screenshot_path)
return output_folder_screenshot_path
-
def convert_screenshots_to_pdf(output_folder_screenshot_path):
- output_pdf_path = f"{OUTPUT_SLIDES_DIR}/{video_path.rsplit('/')[-1].split('.')[0]}" + '.pdf'
+ # Extract the base name from the output folder path
+ base_name = os.path.basename(output_folder_screenshot_path)
+ output_pdf_path = f"{OUTPUT_SLIDES_DIR}/{base_name}.pdf"
print('output_folder_screenshot_path', output_folder_screenshot_path)
print('output_pdf_path', output_pdf_path)
print('converting images to pdf..')
@@ -129,32 +138,35 @@ def convert_screenshots_to_pdf(output_folder_screenshot_path):
f.write(img2pdf.convert(sorted(glob.glob(f"{output_folder_screenshot_path}/*.png"))))
print('Pdf Created!')
print('pdf saved at', output_pdf_path)
+ print('Pdf Created!')
+ print('pdf saved at', output_pdf_path)
if __name__ == "__main__":
-
-# video_path = "./input/Test Video 2.mp4"
-# choice = 'y'
-# output_folder_screenshot_path = initialize_output_folder(video_path)
-
-
parser = argparse.ArgumentParser("video_path")
parser.add_argument("video_path", help="path of video to be converted to pdf slides", type=str)
+ parser.add_argument("-r", "--recursive", action='store_true', help="process all .mp4 files within the specified folder recursively")
args = parser.parse_args()
video_path = args.video_path
-
- print('video_path', video_path)
- output_folder_screenshot_path = initialize_output_folder(video_path)
- detect_unique_screenshots(video_path, output_folder_screenshot_path)
-
- print('Please Manually verify screenshots and delete duplicates')
- while True:
- choice = input("Press y to continue and n to terminate")
- choice = choice.lower().strip()
- if choice in ['y', 'n']:
- break
- else:
- print('please enter a valid choice')
-
- if choice == 'y':
- convert_screenshots_to_pdf(output_folder_screenshot_path)
\ No newline at end of file
+ recursive = args.recursive
+
+ if recursive:
+ # Process all .mp4 files within the specified folder recursively
+ for root, dirs, files in os.walk(video_path):
+ for file in files:
+ if file.endswith(".mp4"):
+ video_file_path = os.path.join(root, file)
+ # Check if a PDF file with the same base name already exists
+ base_name = os.path.splitext(os.path.basename(video_file_path))[0]
+ output_pdf_path = f"{OUTPUT_SLIDES_DIR}/{base_name}.pdf"
+ if os.path.exists(output_pdf_path):
+ print(f'PDF already exists for {base_name}, skipping screenshot detection.')
+ continue
+ output_folder_screenshot_path = initialize_output_folder(video_file_path)
+ detect_unique_screenshots(video_file_path, output_folder_screenshot_path)
+ convert_screenshots_to_pdf(output_folder_screenshot_path)
+ else:
+ # Process a single video file
+ output_folder_screenshot_path = initialize_output_folder(video_path)
+ detect_unique_screenshots(video_path, output_folder_screenshot_path)
+ convert_screenshots_to_pdf(output_folder_screenshot_path)