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brayden-gg
commited on
Commit
•
1b7b649
1
Parent(s):
5e527f9
switched from global vars to State
Browse files
app.py
CHANGED
@@ -7,171 +7,184 @@ from DataLoader import DataLoader
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import convenience
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import gradio as gr
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device = 'cpu'
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num_samples = 10
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net = SynthesisNetwork(weight_dim=256, num_layers=3).to(device)
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if not torch.cuda.is_available():
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net.load_state_dict(torch.load('./model/250000.pt', map_location=torch.device(device))["model_state_dict"])
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dl = DataLoader(num_writer=1, num_samples=10, divider=5.0, datadir='./data/writers')
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writer_options = [5, 14, 15, 16, 17, 22, 25, 80, 120, 137, 147, 151]
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all_loaded_data = []
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chosen_writers = [120, 80]
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avail_char = "0 1 2 3 4 5 6 7 8 9 a b c d e f g h i j k l m n o p q r s t u v w x y z A B C D E F G H I J K L M N O P Q R S T U V W X Y Z ! ? \" ' * + - = : ; , . < > \ / [ ] ( ) # $ % &"
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avail_char_list = avail_char.split(" ")
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for writer_id in chosen_writers:
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loaded_data = dl.next_batch(TYPE='TRAIN', uid=writer_id, tids=list(range(num_samples)))
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all_loaded_data.append(loaded_data)
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default_loaded_data = all_loaded_data[-1]
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# data for writer interpolation
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writer_words = ["hello", "world"]
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writer_mean_Ws = []
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all_word_writer_Ws = []
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all_word_writer_Cs = []
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writer_weight = 0.7
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writer_svg = None
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# data for char interpolation
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blend_chars = ["y", "s"]
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char_mean_global_W = None
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char_weight = 0.7
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default_mean_global_W = convenience.get_mean_global_W(net, default_loaded_data, device)
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char_Ws = default_mean_global_W.reshape(1, 1, convenience.L)
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char_Cs = all_Cs = torch.zeros(1, 2, convenience.L, convenience.L)
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char_svg = None
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# data for MDN
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mdn_words = ["hello", "world"]
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mdn_mean_global_W = None
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all_word_mdn_Ws = []
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all_word_mdn_Cs = []
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mdn_svg = None
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def update_writer_word(target_word):
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writer_words.clear()
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for word in target_word.split(" "):
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writer_words.append(word)
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all_word_writer_Ws.clear()
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all_word_writer_Cs.clear()
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for word in writer_words:
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all_writer_Ws, all_writer_Cs = convenience.get_DSD(net, word, writer_mean_Ws, all_loaded_data, device)
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all_word_writer_Ws.append(all_writer_Ws)
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all_word_writer_Cs.append(all_writer_Cs)
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return update_writer_slider(writer_weight)
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# for writer interpolation
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def update_writer_slider(val):
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global writer_weight
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global writer_svg
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writer_weight = val
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weights = [1 - writer_weight, writer_weight]
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net.clamp_mdn = 0
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return gr.HTML.update(value=writer_svg.tostring()), gr.Slider.update(visible=False), gr.Button.update(visible=True)
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def update_chosen_writers(writer1, writer2):
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net.clamp_mdn = 0
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chosen_writers[0], chosen_writers[1] = int(writer1.split(" ")[1]), int(writer2.split(" ")[1])
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all_loaded_data.clear()
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for writer_id in chosen_writers:
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loaded_data = dl.next_batch(TYPE='TRAIN', uid=writer_id, tids=list(range(num_samples)))
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all_loaded_data.append(loaded_data)
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writer_mean_Ws
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for loaded_data in all_loaded_data:
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mean_global_W = convenience.get_mean_global_W(net, loaded_data, device)
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writer_mean_Ws.append(mean_global_W)
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return gr.Slider.update(label=f"{writer1} vs. {writer2}"), *update_writer_slider(writer_weight)
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def update_writer_download():
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writer_svg.saveas("./DSD_writer_interpolation.svg")
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return gr.File.update(value="./DSD_writer_interpolation.svg", visible=True), gr.Button.update(visible=False)
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# for character blend
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"""Generates an image of handwritten text based on target_sentence"""
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global char_weight
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global char_svg
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net.clamp_mdn = 0
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char_weight = weight
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character_weights = [1 - weight, weight]
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all_W_c = convenience.get_character_blend_W_c(character_weights, char_Ws, char_Cs)
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all_commands = convenience.get_commands(net, blend_chars[0], all_W_c)
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return gr.HTML.update(value=
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def update_blend_chars(c1, c2):
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global blend_chars
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blend_chars[0], blend_chars[1] = c1, c2
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for i in range(2): # get corners of grid
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_, char_matrix = convenience.get_DSD(net, blend_chars[i], default_mean_global_W, [default_loaded_data], device)
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char_Cs[:, i, :, :] = char_matrix
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def update_char_download():
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char_svg.saveas("./DSD_char_interpolation.svg")
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return gr.File.update(value="./DSD_char_interpolation.svg", visible=True), gr.Button.update(visible=False)
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# for MDN
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def update_mdn_word(target_word):
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mdn_words.clear()
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for word in target_word.split(" "):
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mdn_words.append(word)
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all_word_mdn_Ws
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all_word_mdn_Cs
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for word in mdn_words:
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all_writer_Ws, all_writer_Cs = convenience.get_DSD(net, word, default_mean_global_W, [default_loaded_data], device)
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all_word_mdn_Ws.append(all_writer_Ws)
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all_word_mdn_Cs.append(all_writer_Cs)
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return sample_mdn(
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def sample_mdn(maxs, maxr):
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global mdn_svg
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net.clamp_mdn = maxr
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net.scale_sd = maxs
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return gr.HTML.update(value=
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def update_mdn_download():
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mdn_svg.saveas("./DSD_add_randomness.svg")
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return gr.File.update(value="./DSD_add_randomness.svg", visible=True), gr.Button.update(visible=False)
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with gr.Blocks() as demo:
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with gr.Tabs():
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with gr.TabItem("Blend Writers"):
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target_word = gr.Textbox(label="Target Word", value=" ".join(
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with gr.Row():
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left_ratio_options = ["Style " + str(id) for i, id in enumerate(writer_options) if i % 2 == 0]
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right_ratio_options = ["Style " + str(id) for i, id in enumerate(writer_options) if i % 2 == 1]
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with gr.Column():
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writer2 = gr.Radio(right_ratio_options, value="Style 80", label="Style for second writer")
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with gr.Row():
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with gr.Row():
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writer_slider = gr.Slider(0, 1, value=writer_weight, label="Style 120 vs. Style 80")
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with gr.Row():
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writer_default_image = update_writer_slider(
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writer_output = gr.HTML(writer_default_image[0]["value"])
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with gr.Row():
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writer_download_btn = gr.Button("Save to SVG file")
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writer_download = gr.File(interactive=False, show_label=False, visible=False)
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writer_slider.change(fn=update_writer_slider,
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with gr.TabItem("Blend Characters"):
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with gr.Row():
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with gr.Column():
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char1 = gr.Dropdown(choices=avail_char_list, value=
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with gr.Column():
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char2 = gr.Dropdown(choices=avail_char_list, value=
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with gr.Row():
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with gr.Row():
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with gr.Row():
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char_default_image = update_char_slider(char_weight)
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char_output = gr.HTML(char_default_image[0]["value"])
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with gr.Row():
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char_download_btn = gr.Button("Save to SVG file")
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char_download = gr.File(interactive=False, show_label=False, visible=False)
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char_slider.change(fn=update_char_slider,
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char1.change(fn=update_blend_chars,
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char_download_btn.click(fn=update_char_download, inputs=[], outputs=[char_download, char_download_btn], show_progress=True)
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char_download_btn.style(full_width="true")
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with gr.TabItem("Add Randomness"):
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mdn_word = gr.Textbox(label="Target Word", value=" ".join(
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with gr.Row():
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with gr.Column():
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max_rand = gr.Slider(0, 1, value=
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with gr.Column():
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scale_rand = gr.Slider(0, 3, value=
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with gr.Row():
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mdn_sample_button = gr.Button(value="Resample")
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with gr.Row():
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default_im = sample_mdn(
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mdn_output = gr.HTML(default_im[0]["value"])
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with gr.Row():
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randomness_download_btn = gr.Button("Save to SVG file")
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randomness_download = gr.File(interactive=False, show_label=False, visible=False)
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max_rand.change(fn=sample_mdn,
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randomness_download_btn.style(full_width="true")
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demo.launch()
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import convenience
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import gradio as gr
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def update_chosen_writers(writer1, writer2, weight, words, all_loaded_data):
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net.clamp_mdn = 0
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chosen_writers = [int(writer1.split(" ")[1]), int(writer2.split(" ")[1])]
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all_loaded_data = []
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for writer_id in chosen_writers:
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loaded_data = dl.next_batch(TYPE='TRAIN', uid=writer_id, tids=list(range(num_samples)))
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all_loaded_data.append(loaded_data)
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writer_mean_Ws = []
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for loaded_data in all_loaded_data:
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mean_global_W = convenience.get_mean_global_W(net, loaded_data, device)
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writer_mean_Ws.append(mean_global_W.detach())
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return gr.Slider.update(label=f"{writer1} vs. {writer2}"), chosen_writers, writer_mean_Ws, *update_writer_word(" ".join(words), writer_mean_Ws, all_loaded_data, weight)
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def update_writer_word(target_word, writer_mean_Ws, all_loaded_data, writer_weight, device="cpu"):
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words = []
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for word in target_word.split(" "):
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if len(word) > 0:
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words.append(word)
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word_Ws = []
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word_Cs = []
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for word in words:
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writer_Ws, writer_Cs = convenience.get_DSD(net, word, writer_mean_Ws, all_loaded_data, device)
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word_Ws.append(writer_Ws)
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word_Cs.append(writer_Cs)
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if len(words) == 0:
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word_Ws.append(torch.tensor([]))
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word_Cs.append(torch.tensor([]))
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return words, word_Ws, word_Cs, *update_writer_slider(writer_weight, words, word_Ws, word_Cs)
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def update_writer_slider(weight, words, all_word_Ws, all_word_Cs):
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weights = [1 - weight, weight]
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net.clamp_mdn = 0
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svg = convenience.draw_words_svg(words, all_word_Ws, all_word_Cs, weights, net)
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return gr.HTML.update(value=svg.tostring()), gr.File.update(visible=False), gr.Button.update(visible=True), weight, svg
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def update_writer_download(writer_svg):
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writer_svg.saveas("./DSD_writer_interpolation.svg")
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return gr.File.update(value="./DSD_writer_interpolation.svg", visible=True), gr.Button.update(visible=False)
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# for character blend
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def update_blend_chars(c1, c2, weight, char_Ws):
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blend_chars = [c1, c2]
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char_Cs = torch.zeros(1, 2, convenience.L, convenience.L)
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for i in range(2): # get corners of grid
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_, char_matrix = convenience.get_DSD(net, blend_chars[i], default_mean_global_W, [default_loaded_data], device)
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char_Cs[:, i, :, :] = char_matrix
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return gr.Slider.update(label=f"'{c1}' vs. '{c2}'"), char_Cs.detach(), blend_chars, *update_char_slider(weight, char_Ws, char_Cs, blend_chars)
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def update_char_slider(weight, char_Ws, char_Cs, blend_chars):
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"""Generates an image of handwritten text based on target_sentence"""
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net.clamp_mdn = 0
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character_weights = [1 - weight, weight]
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all_W_c = convenience.get_character_blend_W_c(character_weights, char_Ws, char_Cs)
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all_commands = convenience.get_commands(net, blend_chars[0], all_W_c)
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svg = convenience.commands_to_svg(all_commands, 750, 160, 375)
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return gr.HTML.update(value=svg.tostring()), gr.File.update(visible=False), gr.Button.update(visible=True), weight, svg
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def update_char_download(char_svg):
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char_svg.saveas("./DSD_char_interpolation.svg")
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return gr.File.update(value="./DSD_char_interpolation.svg", visible=True), gr.Button.update(visible=False)
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# for MDN
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def update_mdn_word(target_word, scale_sd, clamp_mdn):
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mdn_words = []
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for word in target_word.split(" "):
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mdn_words.append(word)
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86 |
|
87 |
+
all_word_mdn_Ws = []
|
88 |
+
all_word_mdn_Cs = []
|
89 |
for word in mdn_words:
|
90 |
all_writer_Ws, all_writer_Cs = convenience.get_DSD(net, word, default_mean_global_W, [default_loaded_data], device)
|
91 |
all_word_mdn_Ws.append(all_writer_Ws)
|
92 |
all_word_mdn_Cs.append(all_writer_Cs)
|
93 |
|
94 |
+
return mdn_words, all_word_mdn_Ws, all_word_mdn_Cs, *sample_mdn(scale_sd, clamp_mdn, mdn_words, all_word_mdn_Ws, all_word_mdn_Cs)
|
95 |
|
96 |
|
97 |
+
def sample_mdn(maxs, maxr, mdn_words, all_word_mdn_Ws, all_word_mdn_Cs):
|
|
|
98 |
net.clamp_mdn = maxr
|
99 |
net.scale_sd = maxs
|
100 |
+
svg = convenience.draw_words_svg(mdn_words, all_word_mdn_Ws, all_word_mdn_Cs, [1], net)
|
101 |
+
return gr.HTML.update(value=svg.tostring()), gr.File.update(visible=False), gr.Button.update(visible=True), maxr, maxs, svg
|
102 |
|
103 |
+
def update_mdn_download(mdn_svg):
|
104 |
mdn_svg.saveas("./DSD_add_randomness.svg")
|
105 |
return gr.File.update(value="./DSD_add_randomness.svg", visible=True), gr.Button.update(visible=False)
|
106 |
|
107 |
+
device = 'cpu'
|
108 |
+
num_samples = 10
|
109 |
|
110 |
+
net = SynthesisNetwork(weight_dim=256, num_layers=3).to(device)
|
111 |
+
|
112 |
+
if not torch.cuda.is_available():
|
113 |
+
net.load_state_dict(torch.load('./model/250000.pt', map_location=torch.device(device))["model_state_dict"])
|
114 |
+
|
115 |
+
|
116 |
+
dl = DataLoader(num_writer=1, num_samples=10, divider=5.0, datadir='./data/writers')
|
117 |
+
|
118 |
+
writer_options = [5, 14, 15, 16, 17, 22, 25, 80, 120, 137, 147, 151]
|
119 |
+
all_loaded_data_DEFAULT = []
|
120 |
+
chosen_writers_DEFAULT = [120, 80]
|
121 |
+
avail_char = "0 1 2 3 4 5 6 7 8 9 a b c d e f g h i j k l m n o p q r s t u v w x y z A B C D E F G H I J K L M N O P Q R S T U V W X Y Z ! ? \" ' * + - = : ; , . < > \ / [ ] ( ) # $ % &"
|
122 |
+
avail_char_list = avail_char.split(" ")
|
123 |
+
for writer_id in chosen_writers_DEFAULT:
|
124 |
+
loaded_data = dl.next_batch(TYPE='TRAIN', uid=writer_id, tids=list(range(num_samples)))
|
125 |
+
all_loaded_data_DEFAULT.append(loaded_data)
|
126 |
+
|
127 |
+
default_loaded_data = all_loaded_data_DEFAULT[-1]
|
128 |
+
default_mean_global_W = convenience.get_mean_global_W(net, default_loaded_data, device)
|
129 |
+
|
130 |
+
# data for writer interpolation
|
131 |
+
writer_words_DEFAULT = ["hello", "world"]
|
132 |
+
writer_mean_Ws_DEFAULT = []
|
133 |
+
writer_all_word_Ws_DEFAULT = []
|
134 |
+
writer_all_word_Cs_DEFAULT = []
|
135 |
+
writer_weight_DEFAULT = 0.7
|
136 |
+
writer_svg_DEFAULT = None
|
137 |
+
|
138 |
+
# data for char interpolation
|
139 |
+
char_chosen_DEFAULT = ["y", "s"]
|
140 |
+
char_mean_global_W_DEFAULT = None
|
141 |
+
char_weight_DEFAULT = 0.7
|
142 |
+
char_Ws_DEFAULT = default_mean_global_W.reshape(1, 1, convenience.L)
|
143 |
+
char_Cs_DEFAULT = None
|
144 |
+
char_svg_DEFAULT = None
|
145 |
+
|
146 |
+
# # data for MDN
|
147 |
+
mdn_words_DEFAULT = ["hello", "world"]
|
148 |
+
all_word_mdn_Ws_DEFAULT = None
|
149 |
+
all_word_mdn_Cs_DEFAULT = None
|
150 |
+
clamp_mdn_DEFAULT = 0.5
|
151 |
+
scale_sd_DEFAULT = 1
|
152 |
+
mdn_svg_DEFAULT = None
|
153 |
+
|
154 |
+
_wrds, writer_all_word_Ws_DEFAULT, writer_all_word_Cs_DEFAULT, _html, _file, _btn, _wt, _svg = update_writer_word(" ".join(writer_words_DEFAULT), writer_mean_Ws_DEFAULT, all_loaded_data_DEFAULT, writer_weight_DEFAULT)
|
155 |
+
_sldr, _wrtrs, writer_mean_Ws_DEFAULT, _wrds, _waww, _wawc, _html, _file, _btn, _wt, writer_svg_DEFAULT = update_chosen_writers(f"Writer {chosen_writers_DEFAULT[0]}", f"Writer {chosen_writers_DEFAULT[1]}", writer_weight_DEFAULT, writer_words_DEFAULT, all_loaded_data_DEFAULT)
|
156 |
+
|
157 |
+
_wrds, all_word_mdn_Ws_DEFAULT, all_word_mdn_Cs_DEFAULT, _html, _file, _btn, _maxr, _maxs, mdn_svg_DEFAULT = update_mdn_word(" ".join(mdn_words_DEFAULT), scale_sd_DEFAULT, clamp_mdn_DEFAULT)
|
158 |
+
_sldr, char_Cs_DEFAULT, _chrs, _html, _file, _btn, _wght, char_svg_DEFAULT = update_blend_chars(*char_chosen_DEFAULT, char_weight_DEFAULT, char_Ws_DEFAULT)
|
159 |
|
160 |
with gr.Blocks() as demo:
|
161 |
+
all_loaded_data_var = gr.State(all_loaded_data_DEFAULT)
|
162 |
+
chosen_writers_var = gr.State(chosen_writers_DEFAULT)
|
163 |
+
# data for writer interpolation
|
164 |
+
writer_words_var = gr.State(writer_words_DEFAULT)
|
165 |
+
writer_mean_Ws_var = gr.State(writer_mean_Ws_DEFAULT)
|
166 |
+
writer_all_word_Ws_var = gr.State([e.detach() for e in writer_all_word_Ws_DEFAULT])
|
167 |
+
writer_all_word_Cs_var = gr.State([e.detach() for e in writer_all_word_Cs_DEFAULT])
|
168 |
+
writer_weight_var = gr.State(writer_weight_DEFAULT)
|
169 |
+
writer_svg_var = gr.State(writer_svg_DEFAULT)
|
170 |
+
# data for char interpolation
|
171 |
+
char_chosen_var = gr.State(char_chosen_DEFAULT)
|
172 |
+
char_mean_global_W_var = gr.State(char_mean_global_W_DEFAULT)
|
173 |
+
char_weight_var = gr.State(char_weight_DEFAULT)
|
174 |
+
char_Ws_var = gr.State(char_Ws_DEFAULT.detach())
|
175 |
+
char_Cs_var = gr.State(char_Cs_DEFAULT.detach())
|
176 |
+
char_svg_var = gr.State(char_svg_DEFAULT)
|
177 |
+
# # data for MDN
|
178 |
+
mdn_words_var = gr.State(mdn_words_DEFAULT)
|
179 |
+
all_word_mdn_Ws_var = gr.State([e.detach() for e in all_word_mdn_Ws_DEFAULT])
|
180 |
+
all_word_mdn_Cs_var = gr.State([e.detach() for e in all_word_mdn_Cs_DEFAULT])
|
181 |
+
clamp_mdn_var = gr.State(clamp_mdn_DEFAULT)
|
182 |
+
scale_sd_var = gr.State(scale_sd_DEFAULT)
|
183 |
+
mdn_svg_var = gr.State(mdn_svg_DEFAULT)
|
184 |
+
|
185 |
with gr.Tabs():
|
186 |
with gr.TabItem("Blend Writers"):
|
187 |
+
target_word = gr.Textbox(label="Target Word", value=" ".join(writer_words_DEFAULT), max_lines=1)
|
188 |
with gr.Row():
|
189 |
left_ratio_options = ["Style " + str(id) for i, id in enumerate(writer_options) if i % 2 == 0]
|
190 |
right_ratio_options = ["Style " + str(id) for i, id in enumerate(writer_options) if i % 2 == 1]
|
|
|
193 |
with gr.Column():
|
194 |
writer2 = gr.Radio(right_ratio_options, value="Style 80", label="Style for second writer")
|
195 |
with gr.Row():
|
196 |
+
writer_slider = gr.Slider(0, 1, value=writer_weight_DEFAULT, label="Style 120 vs. Style 80")
|
|
|
|
|
197 |
with gr.Row():
|
198 |
+
writer_default_image = update_writer_slider(writer_weight_DEFAULT, writer_words_DEFAULT, writer_all_word_Ws_DEFAULT, writer_all_word_Cs_DEFAULT)
|
199 |
writer_output = gr.HTML(writer_default_image[0]["value"])
|
200 |
with gr.Row():
|
201 |
writer_download_btn = gr.Button("Save to SVG file")
|
202 |
+
writer_download_btn.style(full_width="true")
|
203 |
writer_download = gr.File(interactive=False, show_label=False, visible=False)
|
204 |
+
|
205 |
+
writer_slider.change(fn=update_writer_slider,
|
206 |
+
inputs=[writer_slider, writer_words_var, writer_all_word_Ws_var, writer_all_word_Cs_var],
|
207 |
+
outputs=[writer_output, writer_download, writer_download_btn, writer_weight_var, writer_svg_var], show_progress=False)
|
208 |
+
target_word.submit(fn=update_writer_word,
|
209 |
+
inputs=[target_word, writer_mean_Ws_var, all_loaded_data_var, writer_weight_var],
|
210 |
+
outputs=[writer_words_var, writer_all_word_Ws_var, writer_all_word_Cs_var, writer_output, writer_download, writer_download_btn, writer_weight_var, writer_svg_var], show_progress=False)
|
211 |
+
writer1.change(fn=update_chosen_writers,
|
212 |
+
inputs=[writer1, writer2, writer_weight_var, writer_words_var, all_loaded_data_var],
|
213 |
+
outputs=[writer_slider, chosen_writers_var, writer_mean_Ws_var, writer_words_var, writer_all_word_Ws_var, writer_all_word_Cs_var, writer_output, writer_download, writer_download_btn, writer_weight_var, writer_svg_var])
|
214 |
+
writer2.change(fn=update_chosen_writers,
|
215 |
+
inputs=[writer1, writer2, writer_weight_var, writer_words_var, all_loaded_data_var],
|
216 |
+
outputs=[writer_slider, chosen_writers_var, writer_mean_Ws_var, writer_words_var, writer_all_word_Ws_var, writer_all_word_Cs_var, writer_output, writer_download, writer_download_btn, writer_weight_var, writer_svg_var])
|
217 |
+
writer_download_btn.click(fn=update_writer_download,
|
218 |
+
inputs=[writer_svg_var],
|
219 |
+
outputs=[writer_download, writer_download_btn])
|
220 |
+
|
221 |
with gr.TabItem("Blend Characters"):
|
222 |
with gr.Row():
|
223 |
with gr.Column():
|
224 |
+
char1 = gr.Dropdown(choices=avail_char_list, value=char_chosen_DEFAULT[0], label="Character 1")
|
225 |
with gr.Column():
|
226 |
+
char2 = gr.Dropdown(choices=avail_char_list, value=char_chosen_DEFAULT[1], label="Character 2")
|
227 |
with gr.Row():
|
228 |
+
char_slider = gr.Slider(0, 1, value=char_weight_DEFAULT, label=f"'{char_chosen_DEFAULT[0]}' vs. '{char_chosen_DEFAULT[1]}'")
|
229 |
with gr.Row():
|
230 |
+
char_default_image = update_char_slider(char_weight_DEFAULT, char_Ws_DEFAULT, char_Cs_DEFAULT, char_chosen_DEFAULT)
|
|
|
|
|
231 |
char_output = gr.HTML(char_default_image[0]["value"])
|
232 |
with gr.Row():
|
233 |
char_download_btn = gr.Button("Save to SVG file")
|
234 |
+
char_download_btn.style(full_width="true")
|
235 |
char_download = gr.File(interactive=False, show_label=False, visible=False)
|
236 |
|
237 |
+
char_slider.change(fn=update_char_slider,
|
238 |
+
inputs=[char_slider, char_Ws_var, char_Cs_var, char_chosen_var],
|
239 |
+
outputs=[char_output, char_download, char_download_btn, char_weight_var, char_svg_var], show_progress=False)
|
240 |
|
241 |
+
char1.change(fn=update_blend_chars,
|
242 |
+
inputs=[char1, char2, char_weight_var, char_Ws_var],
|
243 |
+
outputs=[char_slider, char_Cs_var, char_chosen_var, char_output, char_download, char_download_btn, char_weight_var, char_svg_var])
|
244 |
+
char2.change(fn=update_blend_chars,
|
245 |
+
inputs=[char1, char2, char_weight_var, char_Ws_var],
|
246 |
+
outputs=[char_slider, char_Cs_var, char_chosen_var, char_output, char_download, char_download_btn, char_weight_var, char_svg_var])
|
247 |
|
248 |
+
char_download_btn.click(fn=update_char_download,
|
249 |
+
inputs=[char_svg_var],
|
250 |
+
outputs=[char_download, char_download_btn], show_progress=True)
|
251 |
|
|
|
|
|
252 |
with gr.TabItem("Add Randomness"):
|
253 |
+
mdn_word = gr.Textbox(label="Target Word", value=" ".join(mdn_words_DEFAULT), max_lines=1)
|
254 |
with gr.Row():
|
255 |
with gr.Column():
|
256 |
+
max_rand = gr.Slider(0, 1, value=clamp_mdn_DEFAULT, label="Maximum Randomness")
|
257 |
with gr.Column():
|
258 |
+
scale_rand = gr.Slider(0, 3, value=scale_sd_DEFAULT, label="Scale of Randomness")
|
259 |
with gr.Row():
|
260 |
mdn_sample_button = gr.Button(value="Resample")
|
261 |
with gr.Row():
|
262 |
+
default_im = sample_mdn(scale_sd_DEFAULT, clamp_mdn_DEFAULT, mdn_words_DEFAULT, all_word_mdn_Ws_DEFAULT, all_word_mdn_Cs_DEFAULT)
|
263 |
mdn_output = gr.HTML(default_im[0]["value"])
|
264 |
with gr.Row():
|
265 |
randomness_download_btn = gr.Button("Save to SVG file")
|
266 |
randomness_download = gr.File(interactive=False, show_label=False, visible=False)
|
267 |
|
268 |
+
max_rand.change(fn=sample_mdn,
|
269 |
+
inputs=[scale_rand, max_rand, mdn_words_var, all_word_mdn_Ws_var, all_word_mdn_Cs_var],
|
270 |
+
outputs=[mdn_output, randomness_download, randomness_download_btn, clamp_mdn_var, scale_sd_var, mdn_svg_var], show_progress=False)
|
271 |
+
scale_rand.change(fn=sample_mdn,
|
272 |
+
inputs=[scale_rand, max_rand, mdn_words_var, all_word_mdn_Ws_var, all_word_mdn_Cs_var],
|
273 |
+
outputs=[mdn_output, randomness_download, randomness_download_btn, clamp_mdn_var, scale_sd_var, mdn_svg_var], show_progress=False)
|
274 |
+
mdn_sample_button.click(fn=sample_mdn,
|
275 |
+
inputs=[scale_rand, max_rand, mdn_words_var, all_word_mdn_Ws_var, all_word_mdn_Cs_var],
|
276 |
+
outputs=[mdn_output, randomness_download, randomness_download_btn, clamp_mdn_var, scale_sd_var, mdn_svg_var], show_progress=False)
|
277 |
+
|
278 |
+
mdn_word.submit(fn=update_mdn_word,
|
279 |
+
inputs=[mdn_word, scale_sd_var, clamp_mdn_var],
|
280 |
+
outputs=[mdn_words_var, all_word_mdn_Ws_var, all_word_mdn_Cs_var, mdn_output, randomness_download, randomness_download_btn, clamp_mdn_var, scale_sd_var, mdn_svg_var], show_progress=False)
|
281 |
+
|
282 |
+
randomness_download_btn.click(fn=update_mdn_download,
|
283 |
+
inputs=[mdn_svg_var],
|
284 |
+
outputs=[randomness_download, randomness_download_btn])
|
285 |
randomness_download_btn.style(full_width="true")
|
286 |
demo.launch()
|