Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
44ac339
1
Parent(s):
8a48df3
Update app.py
Browse files
app.py
CHANGED
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@@ -34,11 +34,11 @@ model = Blip2ForConditionalGeneration.from_pretrained(
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training_option_settings = {
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"face": {
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"rank":
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"lr_scheduler": "constant",
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"with_prior_preservation": True,
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"class_prompt": "a photo of a person",
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"train_steps_multiplier":
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"file_count": 150,
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"dataset_path": FACES_DATASET_PATH
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},
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@@ -49,12 +49,19 @@ training_option_settings = {
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"class_prompt": "",
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"train_steps_multiplier": 150
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},
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"object": {
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"rank":
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"lr_scheduler": "constant",
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"with_prior_preservation": False,
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"class_prompt": "",
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"train_steps_multiplier":
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},
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"custom": {
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"rank": 32,
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@@ -69,7 +76,7 @@ num_images_settings = {
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#>24 images, 1 repeat; 10<x<24 images 2 repeats; <10 images 3 repeats
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"repeats": [(24, 1), (10, 2), (0, 3)],
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"train_steps_min": 500,
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"train_steps_max":
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}
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def load_captioning(uploaded_images, option):
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@@ -106,6 +113,8 @@ def make_options_visible(option):
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sentence = "A photo of TOK"
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elif option == "style":
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sentence = "in the style of TOK"
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elif option == "custom":
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sentence = "TOK"
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return (
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@@ -522,7 +531,7 @@ with gr.Blocks(css=css, theme=theme) as demo:
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with gr.Column(elem_classes=["main_unlogged"]) as main_ui:
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lora_name = gr.Textbox(label="The name of your LoRA", info="This has to be a unique name", placeholder="e.g.: Persian Miniature Painting style, Cat Toy")
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training_option = gr.Radio(
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label="What are you training?", choices=["object", "style", "face", "custom"]
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)
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concept_sentence = gr.Textbox(
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label="Concept sentence",
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training_option_settings = {
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"face": {
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"rank": 32,
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"lr_scheduler": "constant",
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"with_prior_preservation": True,
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"class_prompt": "a photo of a person",
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"train_steps_multiplier": 150,
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"file_count": 150,
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"dataset_path": FACES_DATASET_PATH
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},
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"class_prompt": "",
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"train_steps_multiplier": 150
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},
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"character": {
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"rank": 32,
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"lr_scheduler": "constant",
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"with_prior_preservation": False,
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"class_prompt": "",
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"train_steps_multiplier": 200
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},
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"object": {
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"rank": 16,
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"lr_scheduler": "constant",
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"with_prior_preservation": False,
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"class_prompt": "",
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"train_steps_multiplier": 50
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},
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"custom": {
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"rank": 32,
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#>24 images, 1 repeat; 10<x<24 images 2 repeats; <10 images 3 repeats
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"repeats": [(24, 1), (10, 2), (0, 3)],
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"train_steps_min": 500,
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"train_steps_max": 1500
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}
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def load_captioning(uploaded_images, option):
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sentence = "A photo of TOK"
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elif option == "style":
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sentence = "in the style of TOK"
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elif option == "character":
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sentence = "A TOK character"
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elif option == "custom":
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sentence = "TOK"
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return (
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with gr.Column(elem_classes=["main_unlogged"]) as main_ui:
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lora_name = gr.Textbox(label="The name of your LoRA", info="This has to be a unique name", placeholder="e.g.: Persian Miniature Painting style, Cat Toy")
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training_option = gr.Radio(
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label="What are you training?", choices=["object", "style", "character", "face", "custom"]
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)
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concept_sentence = gr.Textbox(
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label="Concept sentence",
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