Spaces:

ysharma
/

dummy

Runtime error

dummy / app.py

a2dca9f over 1 year ago

No virus

11.2 kB

	import PIL
	import requests
	import torch
	import gradio as gr
	import random
	from PIL import Image
	import os
	import time
	from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler

	#Loading from Diffusers Library
	model_id = "timbrooks/instruct-pix2pix"
	pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16", safety_checker=None)
	pipe.to("cuda")
	#pipe.enable_attention_slicing()
	pipe.enable_xformers_memory_efficient_attention()
	pipe.unet.to(memory_format=torch.channels_last)

	help_text = """ """

	def previous(image):
	return image

	def upload_image(file):
	return Image.open(file)

	def upload_button_config():
	return gr.update(visible=False)

	def upload_textbox_config(text_in):
	return gr.update(visible=True)

	def dummy_fn():
	return 'dummy'

	def chat(btn_upload, image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid, img_name, counter_out, image_oneup, prompt, history, progress=gr.Progress(track_tqdm=True)):
	progress(0, desc="Starting...")
	if prompt != '' and prompt.lower() == 'reverse' : #--to add revert functionality later
	history = history or []
	temp_img_name = img_name[:-4]+str(int(time.time()))+'.png'
	image_oneup.save(temp_img_name)
	response = 'Reverted to the last image ' + '<img src="/file=' + temp_img_name + '">'
	history.append((prompt, response))
	return history, history, image_oneup, temp_img_name, counter_out
	if prompt != '' and prompt.lower() == 'restart' : #--to add revert functionality later
	history = history or []
	temp_img_name = img_name[:-4]+str(int(time.time()))+'.png'
	#Resizing the image
	basewidth = 512
	wpercent = (basewidth/float(image_in.size[0]))
	hsize = int((float(image_in.size[1])*float(wpercent)))
	image_in = image_in.resize((basewidth,hsize), Image.Resampling.LANCZOS)
	image_in.save(temp_img_name)
	response = 'Reverted to the last image ' + '<img src="/file=' + temp_img_name + '">'
	history.append((prompt, response))
	return history, history, image_in, temp_img_name, counter_out
	#adding supportive sample text
	add_text_list = ["There you go", "Enjoy your image!", "Nice work! Wonder what you gonna do next!", "Way to go!", "Does this work for you?", "Something like this?"]
	if counter_out == 0:
	t1 = time.time()
	print(f"Time at start = {t1}")
	seed = random.randint(0, 1000000)
	img_name = f"./edited_image_{seed}.png"
	#convert file object to image
	image_in = Image.open(btn_upload)
	#Resizing the image
	basewidth = 512
	wpercent = (basewidth/float(image_in.size[0]))
	hsize = int((float(image_in.size[1])*float(wpercent)))
	image_in = image_in.resize((basewidth,hsize), Image.Resampling.LANCZOS)

	#if os.path.exists(img_name):
	# os.remove(img_name)
	#with open(img_name, "wb") as fp:

	# Save the image to the file-like object
	image_in.save(img_name)

	#Get the name of the saved image
	#saved_image_name0 = fp.name

	history = history or []
	response = '<img src="/file=' + img_name + '">'
	history.append((prompt, response))
	counter_out += 1

	t2 = time.time()
	print(f"Time at end = {t2}")
	time_diff = t2-t1
	print(f"Time taken = {time_diff}")
	return history, history, image_in, img_name, counter_out

	elif counter_out == 1:
	#instruct-pix2pix inference
	edited_image = pipe(prompt, image=image_in, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
	if os.path.exists(img_name):
	os.remove(img_name)
	temp_img_name = img_name[:-4]+str(int(time.time()))[-4:] +'.png'
	with open(temp_img_name, "wb") as fp:
	# Save the image to the file-like object
	edited_image.save(fp)
	#Get the name of the saved image
	saved_image_name1 = fp.name
	history = history or []
	response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name1 + '">' #IMG_NAME
	history.append((prompt, response))
	counter_out += 1
	return history, history, edited_image, temp_img_name, counter_out
	elif counter_out > 1:
	edited_image = pipe(prompt, image=image_hid, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
	if os.path.exists(img_name):
	os.remove(img_name)
	temp_img_name = img_name[:-4]+str(int(time.time()))[-4:]+'.png'
	# Create a file-like object
	with open(temp_img_name, "wb") as fp:
	# Save the image to the file-like object
	edited_image.save(fp)
	#Get the name of the saved image
	saved_image_name2 = fp.name
	#edited_image.save(temp_img_name) #, overwrite=True)
	history = history or []
	response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name2 + '">'
	history.append((prompt, response))
	counter_out += 1
	return history, history, edited_image, temp_img_name, counter_out


	#Blocks layout
	with gr.Blocks(css="style.css") as demo:
	with gr.Column(elem_id="col-container") as main_col:
	gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
	<div
	style="
	display: inline-flex;
	align-items: center;
	gap: 0.8rem;
	font-size: 1.75rem;
	"
	>
	<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
	ChatPix2Pix: Image Editing by Instructions
	</h1>
	</div>
	<p style="margin-bottom: 10px; font-size: 94%">
	For faster inference without waiting in the queue, you may duplicate the space and upgrade to GPU in settings <a href="https://huggingface.co/spaces/ysharma/InstructPix2Pix_Chatbot?duplicate=true"><img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
	<a href="https://huggingface.co/timbrooks/instruct-pix2pix" target="_blank">Diffusers implementation of instruct-pix2pix</a> - InstructPix2Pix: Learning to Follow Image Editing Instructions!
	</p>
	</div>""")
	#gr.Markdown("""<h1><center>dummy</h1></center> """)

	with gr.Accordion("Advance settings for Training and Inference", open=False):
	image_in = gr.Image(visible=False,type='pil', label="Original Image")
	gr.Markdown("Advance settings for - Number of Inference steps, Guidanace scale, and Image guidance scale.")
	in_steps = gr.Number(label="Enter the number of Inference steps", value = 20)
	in_guidance_scale = gr.Slider(1,10, step=0.5, label="Set Guidance scale", value=7.5)
	in_img_guidance_scale = gr.Slider(1,10, step=0.5, label="Set Image Guidance scale", value=1.5)
	image_hid = gr.Image(type='pil', visible=False)
	image_oneup = gr.Image(type='pil', visible=False)
	img_name_temp_out = gr.Textbox(visible=False)
	counter_out = gr.Number(visible=False, value=0, precision=0)
	dummy_num = gr.Number(visible=False)

	#with gr.Row():
	text_in = gr.Textbox(value='', Placeholder="Type your instructions here and press enter", elem_id = "input_prompt", visible=False, label='Great! Now you can edit your image with Instructions')
	btn_upload = gr.UploadButton("Upload image", file_types=["image"], file_count="single", elem_id="upload_button")

	chatbot = gr.Chatbot(elem_id = 'chatbot-component')
	state_in = gr.State()

	#text_out_dummy = gr.Textbox(visbile = False, elem_id = 'dummy_elem')

	#btn_upload = gr.UploadButton("Upload image", file_types=["image"], file_count="single", elem_id="upload_button")
	#with gr.Row():
	# btn_upload = gr.UploadButton("Upload image", file_types=["image"], file_count="single", elem_id="upload_button")
	# text_in = gr.Textbox(value='', Placeholder="Enter your instructions here", elem_id = "input_prompt")
	# #btn_upload = gr.UploadButton("Upload image", file_types=["image"], file_count="single", elem_id="upload_button")
	#text_out_dummy = gr.Textbox(visbile = False, elem_id = 'dummy_elem')
	element_dummy = gr.HTML(visbile = False, elem_id = 'dummy_elem')

	#Using Event Listeners
	btn_upload.upload(chat,
	[btn_upload, image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid, img_name_temp_out,counter_out, image_oneup, text_in, state_in],
	[chatbot, state_in, image_in, img_name_temp_out, counter_out])
	btn_upload.upload(fn = upload_textbox_config, inputs=text_in, outputs = text_in)

	text_in.submit(chat,[btn_upload, image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid, img_name_temp_out,counter_out, image_oneup, text_in, state_in], [chatbot, state_in, image_hid, img_name_temp_out, counter_out])
	text_in.submit(previous, [image_hid], [image_oneup])

	chatbot.change(fn = upload_button_config, outputs=btn_upload) #, scroll_to_output = True)
	text_in.submit(None, [], [], _js = "() => document.getElementById('#chatbot-component').scrollTop = document.getElementById('#chatbot-component').scrollHeight")
	#text_in.submit(None, [], main_col, _js = "(x) => x.scrollIntoView(false)")
	#text_in.submit(None, [], main_col, _js = "(x) => x.scrollTo(0, x.scrollHeight)") # or using chatbot
	#text_in.submit(None, [], chatbot, _js = "() => {const element = document.getElementById('#chatbot-component'); element.scrollTop = element.scrollHeight; }")

	#counter_out.click(fn = upload_button_config, outputs=btn_upload)
	#chatbot.change(dummy_fn, inputs=[], outputs=[btn_upload], scroll_to_output = True)
	#gr.Markdown(help_text)
	#text_in.submit(None, [text_in], text_out, _js="(x) => {let newElement = document.createElement('div') newElement.innerHTML = x document.getElementById('chatbot-component').appendChild(newElement) newElement.scrollIntoView() }")
	#text_in.submit(None, [], None, _js="() => {let chatbot = document.getElementById('chatbot-component'); chatbot.scrollTo(0, chatbot.scrollHeight);}")
	#text_in.submit(None, [], None, _js="() => {document.querySelector('#chatbot-component').scrollTop = document.querySelector('#chatbot-component').scrollHeight;}")
	#text_in.submit(None, [], None, _js="() => {let chatbot = document.querySelector('#col-container'); chatbot.scrollTop = chatbot.scrollHeight;}")
	#demo.load(fn = dummy_fn, outputs=text_out_dummy, scroll_to_output = True)
	gr.Markdown(help_text, elem_id = 'help_text')
	#gr.HTML("""<a href="#help_text">Expand/Close</a>""")

	demo.queue(concurrency_count=3)
	demo.launch(debug=True) #, width="80%", height=2000)