Update infer.py

infer.py

@@ -1,193 +1,3 @@
-# import cv2
-# from os.path import isfile, join
-# import subprocess
-# import os
-# from RealESRGAN import RealESRGAN
-# import torch
-# import gradio as gr
-
-# IMAGE_FORMATS = ('.png', '.jpg', '.jpeg', '.tiff', '.bmp', '.gif')
-
-# def inference_image(image, size):
-#     global model2
-#     global model4
-#     global model8
-#     if image is None:
-#         raise gr.Error("Image not uploaded")
-
-#     width, height = image.size
-#     if width >= 5000 or height >= 5000:
-#         raise gr.Error("The image is too large.")
-
-#     if torch.cuda.is_available():
-#         torch.cuda.empty_cache()
-
-#     if size == '2x':
-#         try:
-#             result = model2.predict(image.convert('RGB'))
-#         except torch.cuda.OutOfMemoryError as e:
-#             print(e)
-#             model2 = RealESRGAN(device, scale=2)
-#             model2.load_weights('weights/RealESRGAN_x2.pth', download=False)
-#             result = model2.predict(image.convert('RGB'))
-#     elif size == '4x':
-#         try:
-#             result = model4.predict(image.convert('RGB'))
-#         except torch.cuda.OutOfMemoryError as e:
-#             print(e)
-#             model4 = RealESRGAN(device, scale=4)
-#             model4.load_weights('weights/RealESRGAN_x4.pth', download=False)
-#             result = model2.predict(image.convert('RGB'))
-#     else:
-#         try:
-#             result = model8.predict(image.convert('RGB'))
-#         except torch.cuda.OutOfMemoryError as e:
-#             print(e)
-#             model8 = RealESRGAN(device, scale=8)
-#             model8.load_weights('weights/RealESRGAN_x8.pth', download=False)
-#             result = model2.predict(image.convert('RGB'))
-
-#     print(f"Frame of the Video size ({device}): {size} ... OK")
-#     return result
-
-
-# # assign directory
-# directory = 'videos' #PATH_WITH_INPUT_VIDEOS
-# zee = 0
-
-# def convert_frames_to_video(pathIn,pathOut,fps):
-#     global INPUT_DIR
-#     cap = cv2.VideoCapture(f'/{INPUT_DIR}/videos/input.mp4')
-#     fps = cap.get(cv2.CAP_PROP_FPS)
-#     frame_array = []
-#     files = [f for f in os.listdir(pathIn) if isfile(join(pathIn, f))]
-#     #for sorting the file names properly
-#     files.sort(key = lambda x: int(x[5:-4]))
-#     size2 = (0,0)
-
-#     for i in range(len(files)):
-#         filename=pathIn + files[i]
-#         #reading each files
-#         img = cv2.imread(filename)
-#         height, width, layers = img.shape
-#         size = (width,height)
-#         size2 = size
-#         print(filename)
-#         #inserting the frames into an image array
-#         frame_array.append(img)
-#     out = cv2.VideoWriter(pathOut,cv2.VideoWriter_fourcc(*'DIVX'), fps, size2)
-#     for i in range(len(frame_array)):
-#         # writing to a image array
-#         out.write(frame_array[i])
-#     out.release()
-
-
-# for filename in os.listdir(directory):
-
-#     f = os.path.join(directory, filename)
-#     # checking if it is a file
-#     if os.path.isfile(f):
-
-
-#       print("PROCESSING :"+str(f)+"\n")
-#       # Read the video from specified path
-
-#       #video to frames
-#       cam = cv2.VideoCapture(str(f))
-
-#       try:
-
-#           # PATH TO STORE VIDEO FRAMES
-#           if not os.path.exists(f'/{INPUT_DIR}/upload/'):
-#               os.makedirs(f'/{INPUT_DIR}/upload/')
-
-#       # if not created then raise error
-#       except OSError:
-#           print ('Error: Creating directory of data')
-
-#       # frame
-#       currentframe = 0
-
-
-#       while(True):
-
-#           # reading from frame
-#           ret,frame = cam.read()
-
-#           if ret:
-#               # if video is still left continue creating images
-#               name = f'/{INPUT_DIR}/upload/frame' + str(currentframe) + '.jpg'
-
-#               # writing the extracted images
-#               cv2.imwrite(name, frame)
-
-
-#                 # increasing counter so that it will
-#                 # show how many frames are created
-#               currentframe += 1
-#               print(currentframe)
-#           else:
-#               #deletes all the videos you uploaded for upscaling
-#               #for f in os.listdir(video_folder):
-#               #  os.remove(os.path.join(video_folder, f))
-
-#               break
-
-#         # Release all space and windows once done
-#       cam.release()
-#       cv2.destroyAllWindows()
-
-#       #apply super-resolution on all frames of a video
-
-#       # Specify the directory path
-#       all_frames_path = f"/{INPUT_DIR}/upload/"
-
-#       # Get a list of all files in the directory
-#       file_names = os.listdir(all_frames_path)
-
-#       # process the files
-#       for file_name in file_names:
-#         inference_image(f"/{INPUT_DIR}/upload/{file_name}")
-
-
-#       #convert super res frames to .avi
-#       pathIn = f'/{INPUT_DIR}/results/restored_imgs/'
-
-#       zee = zee+1
-#       fName = "video"+str(zee)
-#       filenameVid = f"{fName}.avi"
-
-#       pathOut = f"/{INPUT_DIR}/results_videos/"+filenameVid
-
-#       convert_frames_to_video(pathIn, pathOut, fps)
-
-
-#       #convert .avi to .mp4
-#       src = f'/{INPUT_DIR}/results_videos/'
-#       dst = f'/{INPUT_DIR}/results_mp4_videos/'
-
-#       for root, dirs, filenames in os.walk(src, topdown=False):
-#           #print(filenames)
-#           for filename in filenames:
-#               print('[INFO] 1',filename)
-#               try:
-#                   _format = ''
-#                   if ".flv" in filename.lower():
-#                       _format=".flv"
-#                   if ".mp4" in filename.lower():
-#                       _format=".mp4"
-#                   if ".avi" in filename.lower():
-#                       _format=".avi"
-#                   if ".mov" in filename.lower():
-#                       _format=".mov"
-
-#                   inputfile = os.path.join(root, filename)
-#                   print('[INFO] 1',inputfile)
-#                   outputfile = os.path.join(dst, filename.lower().replace(_format, ".mp4"))
-#                   subprocess.call(['ffmpeg', '-i', inputfile, outputfile])
-#               except:
-#                   print("An exception occurred")
-
 from PIL import Image
 import cv2 as cv
 import torch