Spaces:
Sleeping
Sleeping
rockeycoss
commited on
Commit
•
1e50ca9
1
Parent(s):
0ab1c76
stable1
Browse files- README.md +1 -1
- app.py +39 -35
- requirements.txt +1 -1
README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: 🖼️🖌️
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colorFrom: yellow
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colorTo: yellow
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: false
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---
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colorFrom: yellow
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colorTo: yellow
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sdk: gradio
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sdk_version: 4.31.1
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app_file: app.py
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pinned: false
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---
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app.py
CHANGED
@@ -1,9 +1,10 @@
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-
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import json
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import webcolors
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import spaces
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import gradio as gr
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import os.path as osp
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from PIL import Image, ImageDraw, ImageFont
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import torch
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@@ -64,6 +65,10 @@ font = ImageFont.truetype("assets/Arial.ttf", 20)
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device = "cuda"
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def import_model_class_from_model_name_or_path(
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pretrained_model_name_or_path: str, revision: str, subfolder: str = "text_encoder",
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):
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@@ -215,6 +220,18 @@ pipeline.scheduler = DPMSolverMultistepScheduler.from_pretrained(
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prompt_format = PromptFormat()
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def get_pixels(
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box_sketch_template,
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evt: gr.SelectData
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return box_sketch_template
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def process_box():
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global stack
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global state
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visibilities = []
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for _ in range(MAX_TEXT_BOX + 1):
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@@ -330,31 +345,19 @@ def process_box():
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# return [gr.update(visible=True), binary_matrixes, *visibilities, *colors]
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return [gr.update(visible=True), *visibilities]
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@
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def generate_image(bg_prompt, bg_class, bg_tags, seed, *conditions):
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print(conditions)
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# 0 load model to cuda
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global pipeline
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if config.pretrained_vae_model_name_or_path is None:
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vae.to(device, dtype=torch.float32)
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else:
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vae.to(device, dtype=inference_dtype)
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text_encoder_one.to(device, dtype=inference_dtype)
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text_encoder_two.to(device, dtype=inference_dtype)
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byt5_model.to(device)
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unet.to(device, dtype=inference_dtype)
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pipeline = pipeline.to(device)
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# 1. parse input
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global state
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global stack
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prompts = []
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colors = []
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font_type = []
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bboxes = []
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num_boxes = len(
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for i in range(num_boxes):
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prompts.append(conditions[i])
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colors.append(conditions[i + MAX_TEXT_BOX])
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@@ -373,10 +376,10 @@ def generate_image(bg_prompt, bg_class, bg_tags, seed, *conditions):
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raise gr.Error(f"Invalid style for text box {i + 1} !")
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bboxes.append(
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[
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-
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-
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(
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(
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]
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)
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styles.append(
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@@ -393,14 +396,11 @@ def generate_image(bg_prompt, bg_class, bg_tags, seed, *conditions):
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bg_prompt += " Tags: " + bg_tags
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text_prompt = prompt_format.format_prompt(prompts, styles)
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print(bg_prompt)
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print(text_prompt)
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# 4. inference
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generator = torch.Generator(device=device)
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else:
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generator = torch.Generator(device=device).manual_seed(seed)
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with torch.cuda.amp.autocast():
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image = pipeline(
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prompt=bg_prompt,
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@@ -411,6 +411,9 @@ def generate_image(bg_prompt, bg_class, bg_tags, seed, *conditions):
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generator=generator,
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text_attn_mask=None,
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).images[0]
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return image
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def process_example(bg_prompt, bg_class, bg_tags, color_str, style_str, text_str, box_str, seed):
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choices=font_idx_list,
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))
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seed_ = gr.Slider(label="Seed", minimum
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button_generate = gr.Button("(2) I've finished my texts, colors and styles, generate!", elem_id="main_button", interactive=True)
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button_layout.click(process_box, inputs=[], outputs=[post_box, *color_row]
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with gr.Column():
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output_image = gr.Image(label="Output Image", interactive=False)
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'LilitaOne, Sensei-Medium, Sensei-Medium, LilitaOne, LilitaOne, LilitaOne',
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"RSVP to +123-456-7890**********Olivia Wilson**********Baby Shower**********Please Join Us For a**********In Honoring**********23 November, 2021 | 03:00 PM Fauget Hotels",
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'[0.07112462006079028, 0.6462006079027356, 0.3373860182370821, 0.026747720364741642]; [0.07051671732522796, 0.38662613981762917, 0.37264437689969604, 0.059574468085106386]; [0.07234042553191489, 0.15623100303951368, 0.6547112462006079, 0.12401215805471125]; [0.0662613981762918, 0.06747720364741641, 0.3981762917933131, 0.035866261398176294]; [0.07051671732522796, 0.31550151975683893, 0.22006079027355624, 0.03951367781155015]; [0.06990881458966565, 0.48328267477203646, 0.39878419452887537, 0.1094224924012158]',
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-
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],
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[
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'The image features a white background with a variety of colorful flowers and decorations. There are several pink flowers scattered throughout the scene, with some positioned closer to the top and others near the bottom. A blue flower can also be seen in the middle of the image. The overall composition creates a visually appealing and vibrant display.',
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@@ -605,6 +608,7 @@ def main():
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],
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outputs=[post_box, box_sketch_template, seed_, *color_row, *colors, *styles, *prompts],
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fn=process_example,
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run_on_click=True,
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label='Examples',
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)
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import gc
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import json
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import webcolors
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import spaces
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import gradio as gr
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import os.path as osp
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from copy import deepcopy
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from PIL import Image, ImageDraw, ImageFont
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import torch
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device = "cuda"
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def flush():
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gc.collect()
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torch.cuda.empty_cache()
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def import_model_class_from_model_name_or_path(
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pretrained_model_name_or_path: str, revision: str, subfolder: str = "text_encoder",
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):
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prompt_format = PromptFormat()
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# move to gpu
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if config.pretrained_vae_model_name_or_path is None:
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vae = vae.to(device, dtype=torch.float32)
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else:
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vae = vae.to(device, dtype=inference_dtype)
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text_encoder_one = text_encoder_one.to(device, dtype=inference_dtype)
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text_encoder_two = text_encoder_two.to(device, dtype=inference_dtype)
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byt5_model = byt5_model.to(device)
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unet = unet.to(device, dtype=inference_dtype)
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pipeline = pipeline.to(device)
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def get_pixels(
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box_sketch_template,
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evt: gr.SelectData
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return box_sketch_template
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def process_box():
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visibilities = []
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for _ in range(MAX_TEXT_BOX + 1):
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# return [gr.update(visible=True), binary_matrixes, *visibilities, *colors]
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return [gr.update(visible=True), *visibilities]
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@torch.inference_mode()
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@spaces.GPU(enable_queue=True)
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def generate_image(bg_prompt, bg_class, bg_tags, seed, *conditions):
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stack_cp = deepcopy(stack)
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print(f"conditions: {conditions}")
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# 1. parse input
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prompts = []
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colors = []
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font_type = []
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bboxes = []
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num_boxes = len(stack_cp) if len(stack_cp[-1]) == 4 else len(stack_cp) - 1
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for i in range(num_boxes):
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prompts.append(conditions[i])
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colors.append(conditions[i + MAX_TEXT_BOX])
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raise gr.Error(f"Invalid style for text box {i + 1} !")
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bboxes.append(
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[
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stack_cp[i][0] / 1024,
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stack_cp[i][1] / 1024,
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(stack_cp[i][2] - stack_cp[i][0]) / 1024,
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(stack_cp[i][3] - stack_cp[i][1]) / 1024,
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]
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)
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styles.append(
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bg_prompt += " Tags: " + bg_tags
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text_prompt = prompt_format.format_prompt(prompts, styles)
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print(f"bg_prompt: {bg_prompt}")
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print(f"text_prompt: {text_prompt}")
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# 4. inference
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generator = torch.Generator(device=device).manual_seed(int(seed))
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with torch.cuda.amp.autocast():
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image = pipeline(
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prompt=bg_prompt,
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generator=generator,
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text_attn_mask=None,
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).images[0]
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+
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flush()
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return image
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def process_example(bg_prompt, bg_class, bg_tags, color_str, style_str, text_str, box_str, seed):
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choices=font_idx_list,
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))
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seed_ = gr.Slider(label="Seed", minimum=0, maximum=2147483647, value=42, step=1)
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button_generate = gr.Button("(2) I've finished my texts, colors and styles, generate!", elem_id="main_button", interactive=True, variant='primary')
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button_layout.click(process_box, inputs=[], outputs=[post_box, *color_row])
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with gr.Column():
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output_image = gr.Image(label="Output Image", interactive=False)
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'LilitaOne, Sensei-Medium, Sensei-Medium, LilitaOne, LilitaOne, LilitaOne',
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"RSVP to +123-456-7890**********Olivia Wilson**********Baby Shower**********Please Join Us For a**********In Honoring**********23 November, 2021 | 03:00 PM Fauget Hotels",
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'[0.07112462006079028, 0.6462006079027356, 0.3373860182370821, 0.026747720364741642]; [0.07051671732522796, 0.38662613981762917, 0.37264437689969604, 0.059574468085106386]; [0.07234042553191489, 0.15623100303951368, 0.6547112462006079, 0.12401215805471125]; [0.0662613981762918, 0.06747720364741641, 0.3981762917933131, 0.035866261398176294]; [0.07051671732522796, 0.31550151975683893, 0.22006079027355624, 0.03951367781155015]; [0.06990881458966565, 0.48328267477203646, 0.39878419452887537, 0.1094224924012158]',
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1,
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],
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[
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'The image features a white background with a variety of colorful flowers and decorations. There are several pink flowers scattered throughout the scene, with some positioned closer to the top and others near the bottom. A blue flower can also be seen in the middle of the image. The overall composition creates a visually appealing and vibrant display.',
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],
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outputs=[post_box, box_sketch_template, seed_, *color_row, *colors, *styles, *prompts],
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fn=process_example,
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cache_examples=False,
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run_on_click=True,
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label='Examples',
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)
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requirements.txt
CHANGED
@@ -7,4 +7,4 @@ torchvision==0.17.0
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deepspeed
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peft
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webcolors
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gradio
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deepspeed
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peft
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webcolors
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gradio==4.31.1
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