import streamlit as st import pickle import pandas as pd import numpy as np import random import torch from matplotlib.backends.backend_agg import RendererAgg from backend.disentangle_concepts import * import torch_utils import dnnlib import legacy _lock = RendererAgg.lock st.set_page_config(layout='wide') BACKGROUND_COLOR = '#bcd0e7' SECONDARY_COLOR = '#bce7db' st.title('Vector algebra using disentangled vectors') st.markdown( """ This page offers the possibility to edit the colors of a given textile image using vector algebra and projections. It allows to select several colors to move towards and against (selecting a positive or negative lambda). Furthermore, it offers the possibility of conditional manipulation, by moving in the direction of a color n1 without affecting the color n2. This is done using a projected direction n1 - (n1.T n2) n2. """, unsafe_allow_html=False,) annotations_file = './data/textile_annotated_files/seeds0000-100000_S.pkl' with open(annotations_file, 'rb') as f: annotations = pickle.load(f) concept_vectors = pd.read_csv('./data/stored_vectors/scores_colors_hsv.csv') concept_vectors['vector'] = [np.array([float(xx) for xx in x]) for x in concept_vectors['vector'].str.split(', ')] concept_vectors['score'] = concept_vectors['score'].astype(float) concept_vectors = concept_vectors.sort_values('score', ascending=False).reset_index() with dnnlib.util.open_url('./data/textile_model_files/network-snapshot-005000.pkl') as f: model = legacy.load_network_pkl(f)['G_ema'].to('cpu') # type: ignore COLORS_LIST = ['Gray', 'Red Orange', 'Yellow', 'Green', 'Light Blue', 'Blue', 'Purple', 'Pink', 'Saturation', 'Value'] COLORS_NEGATIVE = COLORS_LIST + ['None'] if 'image_id' not in st.session_state: st.session_state.image_id = 52921 if 'colors' not in st.session_state: st.session_state.colors = [COLORS_LIST[5], COLORS_LIST[7]] if 'non_colors' not in st.session_state: st.session_state.non_colors = ['None'] if 'color_lambda' not in st.session_state: st.session_state.color_lambda = [5] # ----------------------------- INPUT ---------------------------------- epsilon_container = st.empty() st.header('Image Manipulation with Vector Algebra') header_col_1, header_col_2, header_col_3, header_col_4 = st.columns([1,1,1,1]) input_col_1, output_col_2, output_col_3, input_col_4 = st.columns([1,1,1,1]) # --------------------------- INPUT column 1 --------------------------- with input_col_1: with st.form('image_form'): # image_id = st.number_input('Image ID: ', format='%d', step=1) st.write('**Choose or generate a random image**') chosen_image_id_input = st.empty() image_id = chosen_image_id_input.number_input('Image ID:', format='%d', step=1, value=st.session_state.image_id) choose_image_button = st.form_submit_button('Choose the defined image') random_id = st.form_submit_button('Generate a random image') if random_id: image_id = random.randint(0, 100000) st.session_state.image_id = image_id chosen_image_id_input.number_input('Image ID:', format='%d', step=1, value=st.session_state.image_id) if choose_image_button: image_id = int(image_id) st.session_state.image_id = image_id with header_col_1: st.write('### Input image selection') original_image_vec = annotations['w_vectors'][st.session_state.image_id] img = generate_original_image(original_image_vec, model) with output_col_2: st.image(img) with header_col_2: st.write('### Original image') with input_col_4: with st.form('text_form_1'): st.write('**Colors to vary (including Saturation and Value)**') colors = st.multiselect('Color:', tuple(COLORS_LIST), default=[COLORS_LIST[5], COLORS_LIST[7]]) colors_button = st.form_submit_button('Choose the defined colors') st.session_state.image_id = image_id st.session_state.colors = colors st.session_state.color_lambda = [5]*len(colors) st.session_state.non_colors = ['None']*len(colors) lambdas = [] negative_cols = [] for color in colors: st.write('### '+color ) st.write('**Set range of change (can be negative)**') chosen_color_lambda_input = st.empty() color_lambda = chosen_color_lambda_input.number_input('Lambda:', min_value=-100, step=1, value=5, key=color+'_number') lambdas.append(color_lambda) st.write('**Set dimensions of change to not consider**') chosen_color_negative_input = st.empty() color_negative = chosen_color_negative_input.selectbox('Color:', tuple(COLORS_NEGATIVE), index=len(COLORS_NEGATIVE)-1, key=color+'_noncolor') negative_cols.append(color_negative) lambdas_button = st.form_submit_button('Submit options') if lambdas_button: st.session_state.color_lambda = lambdas st.session_state.non_colors = negative_cols with header_col_4: st.write('### Color settings') # print(st.session_state.colors) # print(st.session_state.color_lambda) # print(st.session_state.non_colors) # ---------------------------- DISPLAY COL 1 ROW 1 ------------------------------ with header_col_3: separation_vectors = [] for col in st.session_state.colors: separation_vector, score_1 = concept_vectors[concept_vectors['color'] == col].reset_index().loc[0, ['vector', 'score']] separation_vectors.append(separation_vector) negative_separation_vectors = [] for non_col in st.session_state.non_colors: if non_col != 'None': negative_separation_vector, score_2 = concept_vectors[concept_vectors['color'] == non_col].reset_index().loc[0, ['vector', 'score']] negative_separation_vectors.append(negative_separation_vector) else: negative_separation_vectors.append('None') ## n1 − (n1T n2)n2 # print(negative_separation_vectors, separation_vectors) st.write('### Output Image') st.write(f'''Change in colors: {str(st.session_state.colors)},\ without affecting colors {str(st.session_state.non_colors)}''') # ---------------------------- DISPLAY COL 2 ROW 1 ------------------------------ with output_col_3: image_updated = generate_composite_images(model, original_image_vec, separation_vectors, lambdas=st.session_state.color_lambda, negative_colors=negative_separation_vectors) st.image(image_updated)