Update app.py

app.py

@@ -1,108 +1,108 @@
-# import gradio as gr
+import gradio as gr
 
-# gr.load("models/black-forest-labs/FLUX.1-schnell").launch()
+gr.load("models/black-forest-labs/FLUX.1-schnell").launch()
 
-import gradio as gr
-import numpy as np
-import random
-import spaces
-import torch
-from diffusers import DiffusionPipeline
+# import gradio as gr
+# import numpy as np
+# import random
+# import spaces
+# import torch
+# from diffusers import DiffusionPipeline
 
-from transformers import pipeline
+# from transformers import pipeline
 
-pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell")
+# pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell")
 
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    generator = torch.Generator().manual_seed(seed)
-    image = pipe(
-            prompt = prompt, 
-            width = width,
-            height = height,
-            num_inference_steps = num_inference_steps, 
-            generator = generator,
-            guidance_scale=0.0
-    ).images[0] 
-    return image, seed
+# def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
+#     if randomize_seed:
+#         seed = random.randint(0, MAX_SEED)
+#     generator = torch.Generator().manual_seed(seed)
+#     image = pipe(
+#             prompt = prompt, 
+#             width = width,
+#             height = height,
+#             num_inference_steps = num_inference_steps, 
+#             generator = generator,
+#             guidance_scale=0.0
+#     ).images[0] 
+#     return image, seed
 
-with gr.Blocks(css=css) as demo:
+# with gr.Blocks(css=css) as demo:
     
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""# FLUX.1 [schnell]
-12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
-[[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
-        """)
+#     with gr.Column(elem_id="col-container"):
+#         gr.Markdown(f"""# FLUX.1 [schnell]
+# 12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
+# [[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
+#         """)
         
-        with gr.Row():
+#         with gr.Row():
             
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+#             prompt = gr.Text(
+#                 label="Prompt",
+#                 show_label=False,
+#                 max_lines=1,
+#                 placeholder="Enter your prompt",
+#                 container=False,
+#             )
             
-            run_button = gr.Button("Run", scale=0)
+#             run_button = gr.Button("Run", scale=0)
         
-        result = gr.Image(label="Result", show_label=False)
+#         result = gr.Image(label="Result", show_label=False)
         
-        with gr.Accordion("Advanced Settings", open=False):
+#         with gr.Accordion("Advanced Settings", open=False):
             
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
+#             seed = gr.Slider(
+#                 label="Seed",
+#                 minimum=0,
+#                 maximum=MAX_SEED,
+#                 step=1,
+#                 value=0,
+#             )
             
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+#             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             
-            with gr.Row():
+#             with gr.Row():
                 
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
+#                 width = gr.Slider(
+#                     label="Width",
+#                     minimum=256,
+#                     maximum=MAX_IMAGE_SIZE,
+#                     step=32,
+#                     value=1024,
+#                 )
                 
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
+#                 height = gr.Slider(
+#                     label="Height",
+#                     minimum=256,
+#                     maximum=MAX_IMAGE_SIZE,
+#                     step=32,
+#                     value=1024,
+#                 )
             
-            with gr.Row():
+#             with gr.Row():
                 
   
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=4,
-                )
+#                 num_inference_steps = gr.Slider(
+#                     label="Number of inference steps",
+#                     minimum=1,
+#                     maximum=50,
+#                     step=1,
+#                     value=4,
+#                 )
         
-        gr.Examples(
-            examples = examples,
-            fn = infer,
-            inputs = [prompt],
-            outputs = [result, seed],
-            cache_examples="lazy"
-        )
+#         gr.Examples(
+#             examples = examples,
+#             fn = infer,
+#             inputs = [prompt],
+#             outputs = [result, seed],
+#             cache_examples="lazy"
+#         )
 
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
-        outputs = [result, seed]
-    )
+#     gr.on(
+#         triggers=[run_button.click, prompt.submit],
+#         fn = infer,
+#         inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
+#         outputs = [result, seed]
+#     )
 
-demo.launch()
+# demo.launch()