Spaces:
Running
on
T4
Running
on
T4
chore: update limits
Browse files
app.py
CHANGED
@@ -60,7 +60,7 @@ samplers_k_diffusion = [
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# ]
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start_time = time.time()
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-
timeout =
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scheduler = DDIMScheduler.from_pretrained(
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base_model,
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@@ -628,7 +628,7 @@ with gr.Blocks(css=css) as demo:
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hr_scale = gr.Slider(
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label="Upscale factor",
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minimum=1.0,
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-
maximum=
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step=0.1,
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value=1.5,
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)
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@@ -646,6 +646,7 @@ with gr.Blocks(css=css) as demo:
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),
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inputs=[hr_enabled, hr_scale, width, height],
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outputs=hr_enabled,
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)
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hr_enabled.change(
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lambda g, x, w, h: gr.Checkbox.update(
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@@ -653,6 +654,7 @@ with gr.Blocks(css=css) as demo:
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),
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inputs=[hr_enabled, hr_scale, width, height],
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outputs=hr_enabled,
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)
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with gr.Tab("Embeddings/Loras"):
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@@ -688,11 +690,13 @@ with gr.Blocks(css=css) as demo:
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add_net,
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inputs=[uploads, ti_state, lora_state],
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outputs=[ti_state, lora_state, ti_vals, lora_vals, uploads],
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)
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btn_del.click(
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clean_states,
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inputs=[ti_state, lora_state],
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outputs=[ti_state, lora_state, ti_vals, lora_vals, uploads],
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)
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# error_output = gr.Markdown()
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@@ -775,26 +779,31 @@ with gr.Blocks(css=css) as demo:
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detect_text,
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inputs=[text, global_stats, width, height],
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outputs=[global_stats, sp, radio, rendered],
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)
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radio.change(
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switch_canvas,
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inputs=[radio, global_stats, width, height],
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outputs=[sp, strength, mask_outsides, rendered],
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)
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sp.edit(
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apply_canvas,
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inputs=[radio, sp, global_stats, width, height],
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outputs=[global_stats, rendered],
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)
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strength.change(
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apply_weight,
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inputs=[radio, strength, global_stats],
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outputs=[global_stats],
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)
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mask_outsides.change(
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apply_option,
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inputs=[radio, mask_outsides, global_stats],
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outputs=[global_stats],
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)
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with gr.Tab("UploadFile"):
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@@ -807,7 +816,7 @@ with gr.Blocks(css=css) as demo:
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mask_outsides2 = gr.Checkbox(
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label="Mask other areas",
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-
value=False
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)
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strength2 = gr.Slider(
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@@ -823,17 +832,20 @@ with gr.Blocks(css=css) as demo:
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apply_image,
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inputs=[sp2, radio, width, height, strength2, mask_outsides2, global_stats],
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outputs=[global_stats, rendered],
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)
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width.change(
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apply_new_res,
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inputs=[width, height, global_stats],
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outputs=[global_stats, rendered],
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)
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height.change(
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apply_new_res,
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inputs=[width, height, global_stats],
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outputs=[global_stats, rendered],
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)
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# color_stats = gr.State(value={})
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# ]
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start_time = time.time()
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+
timeout = 60
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scheduler = DDIMScheduler.from_pretrained(
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base_model,
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hr_scale = gr.Slider(
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label="Upscale factor",
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minimum=1.0,
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+
maximum=2.0,
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step=0.1,
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value=1.5,
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)
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),
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inputs=[hr_enabled, hr_scale, width, height],
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outputs=hr_enabled,
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queue=False,
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)
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hr_enabled.change(
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lambda g, x, w, h: gr.Checkbox.update(
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),
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inputs=[hr_enabled, hr_scale, width, height],
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outputs=hr_enabled,
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+
queue=False,
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)
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with gr.Tab("Embeddings/Loras"):
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add_net,
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inputs=[uploads, ti_state, lora_state],
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outputs=[ti_state, lora_state, ti_vals, lora_vals, uploads],
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+
queue=False,
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)
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btn_del.click(
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clean_states,
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inputs=[ti_state, lora_state],
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outputs=[ti_state, lora_state, ti_vals, lora_vals, uploads],
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+
queue=False,
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)
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# error_output = gr.Markdown()
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detect_text,
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inputs=[text, global_stats, width, height],
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outputs=[global_stats, sp, radio, rendered],
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+
queue=False,
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)
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radio.change(
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switch_canvas,
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inputs=[radio, global_stats, width, height],
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outputs=[sp, strength, mask_outsides, rendered],
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+
queue=False,
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)
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sp.edit(
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apply_canvas,
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inputs=[radio, sp, global_stats, width, height],
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outputs=[global_stats, rendered],
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queue=False,
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)
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strength.change(
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apply_weight,
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inputs=[radio, strength, global_stats],
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outputs=[global_stats],
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queue=False,
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)
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mask_outsides.change(
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apply_option,
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inputs=[radio, mask_outsides, global_stats],
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outputs=[global_stats],
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+
queue=False,
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)
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with gr.Tab("UploadFile"):
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mask_outsides2 = gr.Checkbox(
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label="Mask other areas",
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+
value=False,
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)
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strength2 = gr.Slider(
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apply_image,
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inputs=[sp2, radio, width, height, strength2, mask_outsides2, global_stats],
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outputs=[global_stats, rendered],
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+
queue=False,
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)
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width.change(
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apply_new_res,
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inputs=[width, height, global_stats],
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outputs=[global_stats, rendered],
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+
queue=False,
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)
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height.change(
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apply_new_res,
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inputs=[width, height, global_stats],
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outputs=[global_stats, rendered],
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+
queue=False,
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)
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# color_stats = gr.State(value={})
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