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| import os, datetime, pytz, discord, shutil, requests, subprocess, asyncio | |
| from discord.ext import commands | |
| from time import perf_counter | |
| CLIENT_SECRET = "Ca3tbHTsbImaDmlzXqnpUQLONYtBY1eA" | |
| TOKEN = "OTE5ODk0NDEwODkwNzI3NDg1.G96t2g.XV5efYvSNKqsNvPFxwmviLi-oY6oAYVPTzV78A" | |
| ADMINS = [766145655038410763, 937495666471628831] | |
| basepath = r"C:\Users\Pawin\Software\real-esrgan\discordbot" | |
| def getloggingtime(): | |
| return datetime.datetime.now(pytz.timezone('Asia/Bangkok')).strftime('%d/%m/%Y %H:%M:%S') | |
| def generate_id(path): | |
| return str(len(os.listdir(path))+1).zfill(3) | |
| def file_cleanup(): | |
| dirlist = [fr"{basepath}\input", fr"{basepath}\output"] | |
| for directory in dirlist: | |
| shutil.rmtree(directory) | |
| os.mkdir(directory) | |
| print("BOT: Sucessfully cleaned directories") | |
| file_cleanup() | |
| client = commands.Bot( | |
| command_prefix = "!", | |
| case_insensitive = True, | |
| help_command = None, | |
| activity = discord.Streaming(name = f"/help | Local Instance", url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ") | |
| ) | |
| """BOT EVENTS""" | |
| #Show Status When Bot Is Ready | |
| async def on_ready(): | |
| print('BOT: We have successfully logged in as {0.user}\n'.format(client)) | |
| CurrentlyProcessingJob = False | |
| async def on_message(message): | |
| global CurrentlyProcessingJob | |
| msg = str(message.content) | |
| validMediaChannels = [1083235916354703430, 896342418859892736, 915795164721709077] | |
| channel = message.channel | |
| author = message.author | |
| channelId = int(channel.id) | |
| authorId = int(author.id) | |
| #print(f"Channel id is {channelId}, author id is {authorId}") | |
| imageList = [] | |
| for item in message.attachments: | |
| if item.content_type.startswith("image"): | |
| imageList.append(item.url) | |
| if message.author.bot or msg.startswith("p!"): | |
| pass | |
| elif (authorId in ADMINS) and (channelId in validMediaChannels) and (message.attachments) and (imageList): | |
| print(f'IMAGE: New attachment recieved from {author} in channel {channel}. Processing...') | |
| jobReceiptMessage = await message.reply(f"\nUpscale job received for message {message.id}", mention_author=False) | |
| jobStatusMessage = await message.reply(f"Status: Upscale queued.", mention_author=False) | |
| if CurrentlyProcessingJob: | |
| pendingTemplate = f"__Status__: Upscale %CURRENTSTEP% for job *{message.id}*" | |
| await jobStatusMessage.edit(content=pendingTemplate.replace("%CURRENTSTEP%", "Pending π°οΈ")) | |
| print(f"IMAGE: There is already a job running. Message id {message.id} has been put on queue") | |
| while CurrentlyProcessingJob: | |
| await asyncio.sleep(1) | |
| #wait untill it finishes | |
| await jobStatusMessage.edit(content=pendingTemplate.replace("%CURRENTSTEP%", "Starting π")) | |
| print(f"IMAGE: Starting job {message.id}") | |
| CurrentlyProcessingJob = True | |
| attachmentCount = len(imageList) | |
| multipleImages = attachmentCount > 1 | |
| if multipleImages: | |
| batchstart = perf_counter() | |
| taskType = "Batch Upscale" | |
| else: | |
| taskType = "Image Upscaling" | |
| for i in range(attachmentCount): | |
| """PREPROCESSING""" | |
| fileid = f"{message.id}_{i}" | |
| statusTemplate = f"__Status__: %CURRENTSTEP% image from message *{message.id}* **({i+1}/{attachmentCount})**." | |
| await jobStatusMessage.edit(content=statusTemplate.replace("%CURRENTSTEP%", "π Preprocessing")) | |
| starttime = perf_counter() | |
| url = imageList[i] | |
| extension = url.split(".")[-1] | |
| #fileid = generate_id(f"{basepath}\input") | |
| inputfile = fr"{basepath}\input\{fileid}.{extension}" | |
| outputfile = fr"{basepath}\output\{fileid}.png" | |
| with open (inputfile, "wb") as f: | |
| f.write(requests.get(url).content) | |
| """UPSCALE CONFIG""" | |
| ai_model = "realesrgan-x4plus-anime" | |
| #Can be realesr-animevideov3 (default) | realesrgan-x4plus | realesrgan-x4plus-anime | realesrnet-x4plus | |
| if ai_model == "realesr-animevideov3": | |
| scale = "2" | |
| tilesize = "768" | |
| resizeRequired = False | |
| else: | |
| scale = "4" | |
| tilesize = "256" | |
| resizeRequired = True | |
| #Scale 2 only works with the default model | |
| execute_upscale = fr"C:\Users\Pawin\Software\real-esrgan\realesrgan-ncnn-vulkan.exe -i {inputfile} -o {outputfile} -s {scale} -n {ai_model} -f png -t {tilesize} -j 1:1:1" | |
| """UPSCALING""" | |
| pendtime = perf_counter() | |
| preprocessingtime = round((pendtime-starttime), 2) | |
| print(f"PREPROCESS: Completed in {preprocessingtime}s.\nUPSCALE:") | |
| await jobStatusMessage.edit(content=(statusTemplate.replace("%CURRENTSTEP%", "π§ Upscaling")+"\nThis may take a while...")) | |
| #os.system(execute_upscale) | |
| subprocess.run(execute_upscale, shell=True) | |
| uendtime = perf_counter() | |
| upscaletime = round((uendtime-pendtime),2) | |
| print(f"UPSCALE: Completed in {upscaletime}s.") | |
| """RESIZING""" | |
| if resizeRequired: | |
| await jobStatusMessage.edit(content=statusTemplate.replace("%CURRENTSTEP%", "βοΈ Resizing")) | |
| subprocess.run(f"mogrify -resize 50% {outputfile}", shell=True) | |
| rendtime = perf_counter() | |
| resizingtime = round((rendtime-uendtime), 2) | |
| print(f"RESIZE: Completed in {resizingtime}s.") | |
| else: | |
| resizingtime = 0 | |
| """DELIVERING""" | |
| await jobStatusMessage.edit(content=statusTemplate.replace("%CURRENTSTEP%", "βοΈ Sending")) | |
| try: | |
| #file=discord.File(outputfile) | |
| localImageUrl = f"http://thinkpad.pawin.tk/upscale/{fileid}.png" | |
| #outputImageUrl = jobResultMessage.embeds[0].image.url | |
| #uncomment above to use outside local network | |
| #outputImageUrl = jobResultMessage.attachments[0].url | |
| #print(outputImageUrl) | |
| embed = discord.Embed(title="Upscaled Image", url=localImageUrl, description="Local mode is on. Please use the link above for upscaled image.") | |
| embed.set_author(name=author, icon_url=message.author.avatar_url) | |
| embed.set_image(url=url) | |
| processingstats = f"Preprocessing took {preprocessingtime}s | Resizing took {resizingtime}s." | |
| embed.set_footer(text=f"Took {upscaletime}s to upscale {fileid}.\nUpscaling done with {ai_model}.\n{processingstats}") | |
| await message.channel.send(embed=embed) | |
| except discord.errors.HTTPException as e: | |
| baseErrorMessage = f"There was an error sending the output for image id {fileid}." | |
| if '413 Payload Too Large' in str(e): | |
| await message.reply(f"{baseErrorMessage} It was probably too large for discord to handle.\n```python\n{e}```") | |
| else: | |
| await message.reply(f"{baseErrorMessage}\n```python\n{e}```") | |
| except Exception as e: | |
| await message.reply(f"Encountered an error while processing attachment {fileid}\n```python\n{e}```") | |
| """CLEANING UP""" | |
| #Already finished the whole job. | |
| await jobStatusMessage.edit(content=f"\n__Status__: β Job Completed for all {attachmentCount} attachments from message {message.id} at {getloggingtime()}".replace("all 1 attachments", "an attachment"), mention_author=False) | |
| await message.delete() | |
| await jobReceiptMessage.delete() | |
| await asyncio.sleep(2) | |
| await jobStatusMessage.delete() | |
| print(f"IMAGE: Job finished for messageID {message.id}\n") | |
| CurrentlyProcessingJob = False | |
| else: | |
| print(f"MESSAGE: {channel}- {author}: {msg}") | |
| await client.process_commands(message) | |
| """BOT COMMANDS""" | |
| async def test(ctx): | |
| await ctx.send("Hello!") | |
| async def ping(ctx): | |
| await ctx.send(f'The ping is {round(client.latency * 1000)}ms.') | |
| async def clear(ctx, amount=None): | |
| if ctx.author.id in ADMINS: | |
| if amount == "all": | |
| amount = 100 | |
| elif amount == None: | |
| amount = 2 | |
| else: | |
| amount = int(amount) | |
| await ctx.channel.purge(limit=amount) | |
| await ctx.send(f"Finished clearing {amount} messages {ctx.message.author.mention}", delete_after=4) | |
| else: | |
| await ctx.send('You do not have the permissions to to clear messages using this bot.') | |
| logmsg = f"BOT: Attempting to starting the bot at {getloggingtime()} GMT+7" | |
| print(logmsg) | |
| client.run(TOKEN) |