Create app.py

app.py

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+@title
+import multiprocessing
+import torch
+import os
+from google.colab import output, drive
+from psutil import virtual_memory
+from pathlib import Path
+
+ram_gb = round(virtual_memory().total / 1024**3, 1)
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+from pynvml import *
+nvmlInit()
+h = nvmlDeviceGetHandleByIndex(0)
+info = nvmlDeviceGetMemoryInfo(h)
+
+from translatepy import Translator, Language
+ts = Translator()
+from deep_translator import DeeplTranslator, GoogleTranslator
+from pathlib import Path
+import csv
+import logging
+import requests
+
+#swinir setup
+%matplotlib inline
+%config InlineBackend.figure_format = 'svg'
+%config InlineBackend.rc = {'figure.figsize': (10.0, 10.0)}
+
+!git clone -qq https://github.com/Lin-Sinorodin/SwinIR_wrapper.git
+!pip install -qq timm
+try:
+  from SwinIR_wrapper.SwinIR_wrapper import SwinIR_SR
+except:
+  try:
+    import collections.abc as container_abcs
+    from SwinIR_wrapper.SwinIR_wrapper import SwinIR_SR
+  except:
+    pass
+
+import cv2
+import urllib.request
+import matplotlib.pyplot as plt
+import numpy
+
+#@title
+#!pip install rudalle==0.0.1rc4
+#!git clone https://github.com/neverix/ru-dalle
+!git clone https://github.com/ai-forever/ru-dalle
+!mv -f ru-dalle/* ru-dalle/.git .
+!rm -rf ru-dalle
+#!git checkout better-caching
+!git checkout develop
+!pip install -e .
+!pip install ruclip
+!rm -rf output
+!mkdir output
+output.clear()
+
+!rm -rf output
+!mkdir output
+output.clear()
+
+# Import model
+from rudalle.pipelines import generate_images, show, super_resolution, cherry_pick_by_ruclip
+from rudalle import get_rudalle_model, get_tokenizer, get_vae, get_realesrgan
+from rudalle.utils import seed_everything
+from ruclip import load as get_ruclip
+
+model = get_rudalle_model('Malevich', pretrained=True, fp16=True, device=device)
+vae = get_vae().to('cuda')
+tokenizer = get_tokenizer()