Create inference_video.py
Browse files- inference_video.py +164 -0
inference_video.py
ADDED
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import cv2
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import numpy as np
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import glob
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from os.path import isfile, join
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import subprocess
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from IPython.display import clear_output
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import os
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from google.colab import files
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import shutil
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from io import BytesIO
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import io
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IMAGE_FORMATS = ('.png', '.jpg', '.jpeg', '.tiff', '.bmp', '.gif')
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model_scale = "2" #@param ["2", "4", "8"] {allow-input: false}
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model = RealESRGAN(device, scale=int(model_scale))
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model.load_weights(f'weights/RealESRGAN_x{model_scale}.pth', download=False)
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def process_input(filename):
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result_image_path = os.path.join('results/restored_imgs', os.path.basename(filename))
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image = Image.open(filename).convert('RGB')
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sr_image = model.predict(np.array(image))
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sr_image.save(result_image_path)
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print(f'Finished! Frame of the Video saved to {result_image_path}')
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# assign directory
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directory = 'videos' #PATH_WITH_INPUT_VIDEOS
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zee = 0
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def convert_frames_to_video(pathIn,pathOut,fps):
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frame_array = []
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files = [f for f in os.listdir(pathIn) if isfile(join(pathIn, f))]
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#for sorting the file names properly
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files.sort(key = lambda x: int(x[5:-4]))
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size2 = (0,0)
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for i in range(len(files)):
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filename=pathIn + files[i]
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#reading each files
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img = cv2.imread(filename)
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height, width, layers = img.shape
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size = (width,height)
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size2 = size
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print(filename)
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#inserting the frames into an image array
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frame_array.append(img)
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out = cv2.VideoWriter(pathOut,cv2.VideoWriter_fourcc(*'DIVX'), fps, size2)
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for i in range(len(frame_array)):
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# writing to a image array
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out.write(frame_array[i])
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out.release()
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for filename in os.listdir(directory):
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f = os.path.join(directory, filename)
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# checking if it is a file
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if os.path.isfile(f):
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print("PROCESSING :"+str(f)+"\n")
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# Read the video from specified path
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#video to frames
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cam = cv2.VideoCapture(str(f))
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try:
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# PATH TO STORE VIDEO FRAMES
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if not os.path.exists('upload'):
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os.makedirs('upload')
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# if not created then raise error
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except OSError:
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print ('Error: Creating directory of data')
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# frame
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currentframe = 0
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while(True):
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# reading from frame
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ret,frame = cam.read()
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if ret:
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# if video is still left continue creating images
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name = 'upload/frame' + str(currentframe) + '.jpg'
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# writing the extracted images
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cv2.imwrite(name, frame)
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# increasing counter so that it will
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# show how many frames are created
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currentframe += 1
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print(currentframe)
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else:
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#deletes all the videos you uploaded for upscaling
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#for f in os.listdir(video_folder):
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# os.remove(os.path.join(video_folder, f))
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break
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# Release all space and windows once done
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cam.release()
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cv2.destroyAllWindows()
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#apply super-resolution on all frames of a video
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# Specify the directory path
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all_frames_path = "upload"
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# Get a list of all files in the directory
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file_names = os.listdir(all_frames_path)
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# process the files
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for file_name in file_names:
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process_input(f"upload/{file_name}")
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#convert super res frames to .avi
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pathIn = 'results/restored_imgs/'
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zee = zee+1
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fName = "video"+str(zee)
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filenameVid = f"{fName}.avi"
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pathOut = "results_videos/"+filenameVid
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fps = 25.0 #change this to FPS of your source video
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convert_frames_to_video(pathIn, pathOut, fps)
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#convert .avi to .mp4
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src = 'results_videos/'
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dst = 'results_mp4_videos/'
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for root, dirs, filenames in os.walk(src, topdown=False):
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#print(filenames)
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for filename in filenames:
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print('[INFO] 1',filename)
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try:
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_format = ''
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if ".flv" in filename.lower():
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_format=".flv"
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if ".mp4" in filename.lower():
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_format=".mp4"
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if ".avi" in filename.lower():
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_format=".avi"
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if ".mov" in filename.lower():
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_format=".mov"
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inputfile = os.path.join(root, filename)
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print('[INFO] 1',inputfile)
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outputfile = os.path.join(dst, filename.lower().replace(_format, ".mp4"))
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subprocess.call(['ffmpeg', '-i', inputfile, outputfile])
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except:
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print("An exception occurred")
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