from pathlib import Path from num2words import num2words import numpy as np import os import random import re import torch import json from shapely.geometry.polygon import Polygon from shapely.affinity import scale from PIL import Image, ImageDraw, ImageOps, ImageFilter, ImageFont, ImageColor os.system('pip3 install gradio==3.14.0') import gradio as gr from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM from transformers.models.gptj.modeling_gptj import apply_rotary_pos_emb as apply_rotary_pos_emb_pt tokenizer = AutoTokenizer.from_pretrained("architext/gptj-162M") finetuned = AutoModelForCausalLM.from_pretrained("architext/gptj-162M") device = "cuda:0" if torch.cuda.is_available() else "cpu" print(device) finetuned = finetuned.to(device) # Utility functions def containsNumber(value): for character in value: if character.isdigit(): return True return False def creativity(intensity): if(intensity == 'Low'): top_p = 0.95 top_k = 10 elif(intensity == 'Medium'): top_p = 0.9 top_k = 50 if(intensity == 'High'): top_p = 0.85 top_k = 100 return top_p, top_k housegan_labels = {"living_room": 1, "kitchen": 2, "bedroom": 3, "bathroom": 4, "missing": 5, "closet": 6, "balcony": 7, "corridor": 8, "dining_room": 9, "laundry_room": 10, "corridor": 8} architext_colors = [[0, 0, 0], [249, 222, 182], [195, 209, 217], [250, 120, 128], [126, 202, 234], [190, 0, 198], [255, 255, 255], [6, 53, 17], [17, 33, 58], [132, 151, 246], [197, 203, 159], [6, 53, 17],] regex = re.compile(".*?\((.*?)\)") def draw_polygons(polygons, colors, im_size=(512, 512), b_color="white", fpath=None): image = Image.new("RGBA", im_size, color="white") draw = ImageDraw.Draw(image) for poly, color, in zip(polygons, colors): #get initial polygon coordinates xy = poly.exterior.xy coords = np.dstack((xy[1], xy[0])).flatten() # draw it on canvas, with the appropriate colors draw.polygon(list(coords), fill=(0, 0, 0)) #get inner polygon coordinates small_poly = poly.buffer(-1, resolution=32, cap_style=2, join_style=2, mitre_limit=5.0) if small_poly.geom_type == 'MultiPolygon': mycoordslist = [list(x.exterior.coords) for x in small_poly] for coord in mycoordslist: coords = np.dstack((np.array(coord)[:,1], np.array(coord)[:, 0])).flatten() draw.polygon(list(coords), fill=tuple(color)) elif poly.geom_type == 'Polygon': #get inner polygon coordinates xy2 = small_poly.exterior.xy coords2 = np.dstack((xy2[1], xy2[0])).flatten() # draw it on canvas, with the appropriate colors draw.polygon(list(coords2), fill=tuple(color)) image = image.transpose(Image.FLIP_TOP_BOTTOM) if(fpath): image.save(fpath, quality=100, subsampling=0) return draw, image def prompt_to_layout(user_prompt, intensity, fpath=None): if(containsNumber(user_prompt) == True): spaced_prompt = user_prompt.split(' ') new_prompt = ' '.join([word if word.isdigit() == False else num2words(int(word)).lower() for word in spaced_prompt]) model_prompt = '[User prompt] {} [Layout]'.format(new_prompt) top_p, top_k = creativity(intensity) model_prompt = '[User prompt] {} [Layout]'.format(user_prompt) input_ids = tokenizer(model_prompt, return_tensors='pt').to(device) output = finetuned.generate(**input_ids, do_sample=True, top_p=top_p, top_k=top_k, eos_token_id=50256, max_length=400) output = tokenizer.batch_decode(output, skip_special_tokens=True) layout = output[0].split('[User prompt]')[1].split('[Layout] ')[1].split(', ') spaces = [txt.split(':')[0] for txt in layout] coords = [] for txt in layout: if ':' in txt: split_txt = txt.split(':') coords.append(split_txt[1].rstrip()) coordinates = [re.findall(regex, coord) for coord in coords] # Initialize an empty list to store the numerical coordinates num_coords = [] # Iterate over each coordinate in the coordinates list for coord in coordinates: temp = [] # Temporary list to store the cleaned numbers # Split the coordinate into individual numbers for xy in coord: numbers = xy.split(',') # Clean each number and convert it to an integer for num in numbers: clean_num = re.sub(r'^\D*|\D*$', '', num) # Remove non-digit characters # Check if the cleaned number is a digit if clean_num.isdigit(): # Convert the cleaned number to an integer and divide it by 14.2 # If division by zero occurs, skip this number try: temp.append(int(clean_num)/14.2) except ZeroDivisionError: continue # Skip this number and continue with the next one # Append the temporary list to the num_coords list num_coords.append(temp) new_spaces = [] for i, v in enumerate(spaces): totalcount = spaces.count(v) count = spaces[:i].count(v) new_spaces.append(v + str(count + 1) if totalcount > 1 else v) out_dict = dict(zip(new_spaces, num_coords)) out_dict = json.dumps(out_dict) polygons = [] for coord in coordinates: polygons.append([point.split(',') for point in coord]) geom = [] for poly in polygons: new_poly = [list(map(int, point)) for point in poly] if len(new_poly) >= 4: scaled_poly = scale(Polygon(new_poly), xfact=2, yfact=2, origin=(0,0)) geom.append(scaled_poly) colors: List[int] = [] for space in spaces: for key in housegan_labels.keys(): if key in space: colors.append(architext_colors[housegan_labels[key]]) break _, im = draw_polygons(geom, colors, fpath=fpath) html = '' legend = Image.open("labels.png") imgs_comb = np.vstack([im, legend]) imgs_comb = Image.fromarray(imgs_comb) return imgs_comb, out_dict # Gradio App custom_css=""" @import url("https://use.typekit.net/nid3pfr.css"); .gradio_wrapper .gradio_bg[is_embedded=false] { min-height: 80%; } .gradio_wrapper .gradio_bg[is_embedded=false] .gradio_page { display: flex; width: 100vw; min-height: 50vh; flex-direction: column; justify-content: center; align-items: center; margin: 0px; max-width: 100vw; background: #FFFFFF; } .gradio_wrapper .gradio_bg[is_embedded=false] .gradio_page .content { padding: 0px; margin: 0px; } .gradio_interface { width: 100vw; max-width: 1500px; } .gradio_interface .panel:nth-child(2) .component:nth-child(3) { display:none } .gradio_wrapper .gradio_bg[theme=default] .panel_buttons { justify-content: flex-end; } .gradio_wrapper .gradio_bg[theme=default] .panel_button { flex: 0 0 0; min-width: 150px; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .panel_button.submit { background: #11213A; border-radius: 5px; color: #FFFFFF; text-transform: uppercase; min-width: 150px; height: 4em; letter-spacing: 0.15em; flex: 0 0 0; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .panel_button.submit:hover { background: #000000; } .input_text:focus { border-color: #FA7880; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .input_text input, .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .input_text textarea { font: 200 45px garamond-premier-pro-display, serif; line-height: 110%; color: #11213A; border-radius: 5px; padding: 15px; border: none; background: #F2F4F4; } .input_text textarea:focus-visible { outline: none; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .input_radio .radio_item.selected { background-color: #11213A; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .input_radio .selected .radio_circle { border-color: #4365c4; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .output_image { width: 100%; height: 40vw; max-height: 630px; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .output_image .image_preview_holder { background: transparent; } .panel:nth-child(1) { margin-left: 50px; margin-right: 50px; margin-bottom: 80px; max-width: 750px; } .panel { background: transparent; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .component_set { background: transparent; box-shadow: none; } .panel:nth-child(2) .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .panel_header { display: none; } .gradio_wrapper .gradio_bg[is_embedded=false] .gradio_page .footer { transform: scale(0.75); filter: grayscale(1); } .labels { height: 20px; width: auto; } @media (max-width: 1000px){ .panel:nth-child(1) { margin-left: 0px; margin-right: 0px; } .gradio_wrapper .gradio_bg[theme=default] .gradio_interface .output_image { height: auto; } } """ creative_slider = gr.inputs.Radio(["Low", "Medium", "High"], default="Low", label='Creativity') textbox = gr.inputs.Textbox(placeholder='An apartment with two bedrooms and one bathroom', lines="3", label="DESCRIBE YOUR IDEAL APARTMENT") generated = gr.outputs.Image(label='Generated Layout', type='numpy') layout = gr.outputs.Textbox(label='Layout Coordinates') examples = [ ["two bedrooms and two bathrooms", "Low"], ["three bedrooms with a kitchen adjacent to the dining room", "Medium"] ] def retry_prompt_to_layout(user_prompt, intensity, fpath=None): max_attempts = 5 attempts = 0 while attempts < max_attempts: try: # Call the original function result = prompt_to_layout(user_prompt, intensity, fpath) return result except Exception as e: print(f"Attempt {attempts+1} failed with error: {e}") attempts += 1 iface = gr.Interface(fn=retry_prompt_to_layout, inputs=[textbox, creative_slider], outputs=[generated, layout], css=custom_css, theme="default", allow_flagging='never', allow_screenshot=False, thumbnail="thumbnail_gradio.PNG", examples=examples) iface.launch(enable_queue=True)