Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
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@@ -8,6 +8,8 @@ import numpy as np
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import spaces
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import torch
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import random
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from PIL import Image
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from diffusers import FluxKontextPipeline
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@@ -22,6 +24,7 @@ optimize_pipeline_(pipe, image=Image.new("RGB", (512, 512)), prompt='prompt')
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@spaces.GPU(duration=24)
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def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5, steps=28, progress=gr.Progress(track_tqdm=True)):
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"""
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Perform image editing using the FLUX.1 Kontext pipeline.
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@@ -82,11 +85,15 @@ def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5
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num_inference_steps=steps,
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generator=torch.Generator().manual_seed(seed),
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).images[0]
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return image, seed, gr.Button(visible=True)
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@spaces.GPU(duration=25)
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def infer_example(input_image, prompt):
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image, seed, _ = infer(input_image, prompt)
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return image, seed
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css="""
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import spaces
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import torch
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import random
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import time
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from datetime import timedelta as td
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from PIL import Image
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from diffusers import FluxKontextPipeline
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@spaces.GPU(duration=24)
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def infer(input_image, prompt, seed=42, randomize_seed=False, guidance_scale=2.5, steps=28, progress=gr.Progress(track_tqdm=True)):
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start_load = time.time()
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"""
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Perform image editing using the FLUX.1 Kontext pipeline.
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num_inference_steps=steps,
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generator=torch.Generator().manual_seed(seed),
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).images[0]
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print(f"Time Elapsed: {td(seconds=int(time.time() - start_load))}")
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return image, seed, gr.Button(visible=True)
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@spaces.GPU(duration=25)
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def infer_example(input_image, prompt):
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start_load = time.time()
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image, seed, _ = infer(input_image, prompt)
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print(f"Time Elapsed: {td(seconds=int(time.time() - start_load))}")
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return image, seed
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css="""
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