Spaces:
Runtime error
Runtime error
import streamlit as st | |
from streamlit_drawable_canvas import st_canvas | |
from PIL import Image | |
from typing import Union | |
import random | |
import numpy as np | |
import os | |
import time | |
# get OS environment variables of EMULATED | |
EMULATED = os.environ.get('EMULATED', False) | |
print(EMULATED) | |
if not EMULATED: | |
from models import make_image_controlnet, make_inpainting, segment_image | |
else: | |
from models_stub import make_image_controlnet, make_inpainting, segment_image | |
from config import HEIGHT, WIDTH, POS_PROMPT, NEG_PROMPT, COLOR_MAPPING, map_colors, map_colors_rgb | |
from palette import COLOR_MAPPING_CATEGORY | |
from preprocessing import preprocess_seg_mask, get_image, get_mask | |
# wide layout | |
st.set_page_config(layout="wide") | |
def on_upload() -> None: | |
"""Upload image to the canvas.""" | |
if 'input_image' in st.session_state and st.session_state['input_image'] is not None: | |
image = Image.open(st.session_state['input_image']).convert('RGB') | |
st.session_state['initial_image'] = image | |
# st.session_state['history'] = [{'image': image.resize((512, 512)), | |
# 'message': "initial image", | |
# "positive_prompt": "", | |
# "negative_prompt": "", | |
# "index": 0}] | |
def check_reset_state() -> bool: | |
"""Check whether the UI elements need to be reset | |
Returns: | |
bool: True if the UI elements need to be reset, False otherwise | |
""" | |
if ('reset_canvas' in st.session_state and st.session_state['reset_canvas']): | |
st.session_state['reset_canvas'] = False | |
return True | |
st.session_state['reset_canvas'] = False | |
return False | |
def move_image(source: Union[str, Image.Image], | |
dest: str, | |
rerun: bool = True, | |
remove_state: bool = True) -> None: | |
"""Move image from source to destination. | |
Args: | |
source (Union[str, Image.Image]): source image | |
dest (str): destination image location | |
rerun (bool, optional): rerun streamlit. Defaults to True. | |
remove_state (bool, optional): remove the canvas state. Defaults to True. | |
""" | |
source_image = source if isinstance(source, Image.Image) else st.session_state[source] | |
if remove_state: | |
st.session_state['reset_canvas'] = True | |
st.session_state[dest] = source_image | |
if rerun: | |
st.experimental_rerun() | |
def on_change_radio() -> None: | |
"""Reset the UI elements when the radio button is changed.""" | |
st.session_state['reset_canvas'] = True | |
def make_canvas_dict(canvas_color, brush, paint_mode, _reset_state): | |
canvas_dict = dict( | |
fill_color=canvas_color, | |
stroke_color=canvas_color, | |
background_color="#FFFFFF", | |
background_image=st.session_state['initial_image'] if 'initial_image' in st.session_state else None, | |
stroke_width=brush, | |
initial_drawing={'version': '4.4.0', 'objects': []} if _reset_state else None, | |
update_streamlit=True, | |
height=512, | |
width=512, | |
drawing_mode=paint_mode, | |
key="canvas", | |
) | |
return canvas_dict | |
def make_prompt_row(): | |
col_0_0, col_0_1 = st.columns(2) | |
with col_0_0: | |
st.text_input(label="Positive prompt", value="", key='positive_prompt') | |
with col_0_1: | |
st.text_input(label="Negative prompt", value="", key='negative_prompt') | |
def make_sidebar(): | |
with st.sidebar: | |
input_image = st.file_uploader("", type=["png", "jpg"], key='input_image', on_change=on_upload) | |
generation_mode = st.selectbox("Generation mode", ["Segmentation conditioning", "Inpainting"], on_change=on_change_radio) | |
paint_mode = st.sidebar.selectbox("Painting mode", ("freedraw", "polygon")) | |
if paint_mode == "freedraw": | |
brush = st.slider("Stroke width", 5, 140, 100, key='slider_seg') | |
else: | |
brush = 5 | |
if generation_mode == "Segmentation conditioning": | |
category_chooser = st.sidebar.selectbox("Filter on category", list( | |
COLOR_MAPPING_CATEGORY.keys()), index=0, key='category_chooser') | |
chosen_colors = list(COLOR_MAPPING_CATEGORY[category_chooser].keys()) | |
color_chooser = st.sidebar.selectbox( | |
"Choose a color", chosen_colors, index=0, format_func=map_colors, key='color_chooser' | |
) | |
else: | |
color_chooser = "#000000" | |
return input_image, generation_mode, brush, color_chooser, paint_mode | |
def make_output_image(): | |
if 'output_image' in st.session_state: | |
output_image = st.session_state['output_image'] | |
if isinstance(output_image, np.ndarray): | |
output_image = Image.fromarray(output_image) | |
if isinstance(output_image, Image.Image): | |
output_image = output_image.resize((512, 512)) | |
else: | |
output_image = Image.new('RGB', (512, 512), (255, 255, 255)) | |
st.write("#### Output image") | |
st.image(output_image, width=512) | |
if st.button("Move to input image"): | |
move_image('output_image', 'initial_image', remove_state=True, rerun=True) | |
def make_editing_canvas(canvas_color, brush, _reset_state, generation_mode, paint_mode): | |
st.write("#### Input image") | |
canvas_dict = make_canvas_dict( | |
canvas_color=canvas_color, | |
paint_mode=paint_mode, | |
brush=brush, | |
_reset_state=_reset_state | |
) | |
if generation_mode == "Segmentation conditioning": | |
canvas = st_canvas( | |
**canvas_dict, | |
) | |
if 'seg' not in st.session_state: | |
with st.spinner(text="Preparing image segmentation"): | |
image = get_image() | |
print("Preparing image segmentation") | |
real_seg = np.array(segment_image(Image.fromarray(image))) | |
st.session_state['seg'] = real_seg | |
# get unique RGB colors from this segmentation map | |
st.image(Image.fromarray(real_seg), width=512) | |
print(real_seg.shape) | |
unique_colors = np.unique(real_seg.reshape(-1, real_seg.shape[2]), axis=0) | |
unique_colors = [tuple(color) for color in unique_colors] | |
print(unique_colors) | |
st.session_state['unique_colors'] = unique_colors | |
# multiselect to choose multiple colors | |
chosen_colors = st.multiselect( | |
label="Choose colors", options=unique_colors, default=None, key='unique_colors', format_func=map_colors_rgb | |
) | |
print(chosen_colors) | |
if st.button("generate image", key='generate_button'): | |
image = get_image() | |
print("Preparing image segmentation") | |
real_seg = segment_image(Image.fromarray(image)) | |
mask, seg = preprocess_seg_mask(canvas, real_seg) | |
with st.spinner(text="Generating image"): | |
print("Making image") | |
result_image = make_image_controlnet(image=image, | |
mask_image=mask, | |
controlnet_conditioning_image=seg, | |
positive_prompt=st.session_state['positive_prompt'], | |
negative_prompt=st.session_state['negative_prompt'], | |
seed=random.randint(0, 100000) # nosec | |
)[0] | |
if isinstance(result_image, np.ndarray): | |
result_image = Image.fromarray(result_image) | |
st.session_state['output_image'] = result_image | |
elif generation_mode == "Inpainting": | |
image = get_image() | |
canvas = st_canvas( | |
**canvas_dict, | |
) | |
if st.button("generate images", key='generate_button'): | |
canvas_mask = canvas.image_data | |
if not isinstance(canvas_mask, np.ndarray): | |
canvas_mask = np.array(canvas_mask) | |
mask = get_mask(canvas_mask) | |
with st.spinner(text="Generating new images"): | |
print("Making image") | |
result_image = make_inpainting(positive_prompt=st.session_state['positive_prompt'], | |
image=image, | |
mask_image=mask, | |
negative_prompt=st.session_state['negative_prompt'], | |
)[0] | |
if isinstance(result_image, np.ndarray): | |
result_image = Image.fromarray(result_image) | |
st.session_state['output_image'] = result_image | |
def main(): | |
# center text | |
st.write("## Controlnet sprint - interior design", unsafe_allow_html=True) | |
input_image, generation_mode, brush, color_chooser, paint_mode = make_sidebar() | |
# check if there is an input_image | |
if not ('input_image' in st.session_state and st.session_state['input_image'] is not None): | |
print("Image not present") | |
st.success("Upload an image to start") | |
else: | |
make_prompt_row() | |
_reset_state = check_reset_state() | |
col1, col2 = st.columns(2) | |
with col1: | |
make_editing_canvas(canvas_color=color_chooser, | |
brush=brush, | |
_reset_state=_reset_state, | |
generation_mode=generation_mode, | |
paint_mode=paint_mode | |
) | |
with col2: | |
make_output_image() | |
if __name__ == "__main__": | |
main() |