Processing movie (AEV, MP4) in KNIME

KNIME Extensions
5

So resurrecting this thread and investigating @Andrew_Steel suggestion, opencv will do the job. The following python code saves every nth image to a temp folder, having scaled it down. The scale factor, output format (png or jpg) and n are determined by user inputs:

# Copy input to output
output_table_1 = input_table_1.copy()

import cv2
from io import BytesIO

imgCol = []
i = 0

for x in range(len(input_table_1['Path'])):
    cap = cv2.VideoCapture(input_table_1['Path'][x])
    images = []
    while(cap.isOpened()):
        ret, frame = cap.read()
        if ret == False:
            break
        outPath = flow_variables['temp_dir_path_location']+"/" + input_table_1['outName'][x] + "_" + str(i) +"." + flow_variables['imgFormat']
        i = i + 1
        if i % flow_variables['nthFrame'] == 0:
            newDim = (int(frame.shape[1] * flow_variables['thumbnailScale'] / 100), int(frame.shape[0] * flow_variables['thumbnailScale'] / 100))
            frame = cv2.resize(frame, newDim, interpolation=cv2.INTER_AREA) 
            cv2.imwrite(outPath, frame)
            images.append(outPath)
        #is_success, buffer = cv2.imencode(".png", frame)
        #io_buf = BytesIO(buffer)
        #images = io_buf.getvalue()
    imgCol.append(images)


output_table_1['frames']=imgCol

Notes:

  1. The commentated out code was me trying to write the blobs directly to the output table which KNIME can’t do yet!
  2. Apologies to the pythonistas out there who could probably make this much more elegant - I inhabit the java world by day and cobbled this together from various examples and looking up things that are probably elementary in python-speak

Thanks again,

Steve

PS - anyone want to flick through several thousand thumbnails to spot the interesting wildlife that the webcam caught in amidst the videos of blowing leaves, rain etc etc?!

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