update seeding

app.py

@@ -1,10 +1,10 @@
 import gradio as gr
 import torch
 import spaces
-
 from huggingface_hub import hf_hub_download
 from diffusers import FluxControlPipeline, FluxTransformer2DModel
 import numpy as np
+
 ####################################
 #   Load the model(s) on GPU       #
 ####################################
@@ -17,12 +17,15 @@ pipeline.load_lora_weights(
     hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"), adapter_name="hyper-sd"
 )
 pipeline.set_adapters(["hyper-sd"], adapter_weights=[0.125])
+
 MAX_SEED = np.iinfo(np.int32).max
+
 def get_seed(randomize_seed: bool, seed: int) -> int:
     """
     Get the random seed.
     """
-    return np.random.randint(0, MAX_SEED) if randomize_seed else seed
+    return int(np.random.randint(0, MAX_SEED) if randomize_seed else seed)
+
 #####################################
 #  The function for our Gradio app  #
 #####################################
@@ -30,21 +33,25 @@ def get_seed(randomize_seed: bool, seed: int) -> int:
 def generate(prompt, input_image, seed, progress=gr.Progress(track_tqdm=True)):
     """
     Runs the Flux Control pipeline for editing the given `input_image`
-    with the specified `prompt`. The pipeline is on CPU by default.
+    with the specified `prompt`. The pipeline is on GPU by default.
     """
-    output_image = pipeline(
-        control_image=input_image,
-        prompt=prompt,
-        guidance_scale=30.,
-        num_inference_steps=8,
-        max_sequence_length=512,
-        height=input_image.height,
-        width=input_image.width,
-        generator=torch.manual_seed(seed)
-    ).images[0]
+    seed = int(seed)  # Ensure seed is an integer
+    generator = torch.Generator(device="cuda").manual_seed(seed)  # Maintain reproducibility
 
-    return output_image
+    with progress.tqdm(total=1, desc="Generating Image") as pbar:
+        output_image = pipeline(
+            control_image=input_image,
+            prompt=prompt,
+            guidance_scale=30.,
+            num_inference_steps=8,
+            max_sequence_length=512,
+            height=input_image.height,
+            width=input_image.width,
+            generator=generator  # Pass the seeded generator
+        ).images[0]
+        pbar.update(1)  # Update progress bar
 
+    return output_image
 
 def launch_app():
     css = '''
@@ -54,7 +61,6 @@ def launch_app():
         gr.Markdown(
             """
             # Flux Control Editing 🖌️
-
             Edit any image with the [FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) 
             [Flux Control edit framework](https://github.com/sayakpaul/flux-image-editing) by [Sayak Paul](https://huggingface.co/sayakpaul).
             """
@@ -78,10 +84,10 @@ def launch_app():
 
         # Connect button to function
         generate_button.click(
-        get_seed,
-        inputs=[randomize_seed, seed],
-        outputs=[seed],
-    ).then(
+            get_seed,
+            inputs=[randomize_seed, seed],
+            outputs=[seed],
+        ).then(
             fn=generate,
             inputs=[prompt, input_image, seed],
             outputs=[output_image],
@@ -107,7 +113,6 @@ def launch_app():
         )
     return demo
 
-
 if __name__ == "__main__":
     demo = launch_app()
     demo.launch()