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README.md

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----
-title: SURPRISE WITH IMAGES
-emoji: 🏃
-colorFrom: pink
-colorTo: pink
-sdk: gradio
-sdk_version: 5.0.1
-app_file: app.py
-pinned: false
-short_description: 'WE CAN GENERATE MANY UNFORESEEN ,AMAZING PICTURES '
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: GET AMAZING IMAGES
+emoji: ⚡
+colorFrom: green
+colorTo: indigo
+sdk: gradio
+sdk_version: 4.44.1
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from gradio_client import Client
+import random
+
+# Initialize the client for the Hugging Face Space
+client = Client("ByteDance/Hyper-FLUX-8Steps-LoRA")
+
+def generate_image(prompt, height, width, steps, scales, seed):
+    """
+    Generates an image based on the provided parameters by calling the Hugging Face Space API.
+
+    Parameters:
+    - prompt (str): The text prompt for image generation.
+    - height (int): The height of the generated image.
+    - width (int): The width of the generated image.
+    - steps (int): The number of steps for the image generation process.
+    - scales (float): The scaling factor.
+    - seed (int): The seed for random number generation to ensure reproducibility.
+
+    Returns:
+    - result (str or Image): The generated image or a link to it.
+    """
+    # Generate a random seed if not provided
+    if not seed:
+        seed = random.randint(0, 100000)
+
+    try:
+        result = client.predict(
+            height=int(height),
+            width=int(width),
+            steps=int(steps),
+            scales=float(scales),
+            prompt=prompt,
+            seed=int(seed),
+            api_name="/process_image"
+        )
+        return result
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Hyper-FLUX-8Steps-LoRA Image Generator")
+    gr.Markdown("Generate images based on your text prompts using the Hyper-FLUX-8Steps-LoRA model.")
+
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Enter your descriptive text here...",
+                lines=2
+            )
+            height = gr.Number(
+                label="Height",
+                value=1024,
+                precision=0,
+                interactive=True
+            )
+            width = gr.Number(
+                label="Width",
+                value=1024,
+                precision=0,
+                interactive=True
+            )
+            steps = gr.Number(
+                label="Steps",
+                value=8,
+                precision=0,
+                interactive=True
+            )
+            scales = gr.Number(
+                label="Scale",
+                value=3.5,
+                precision=1,
+                interactive=True
+            )
+            seed = gr.Number(
+                label="Seed",
+                value=3413,
+                precision=0,
+                interactive=True
+            )
+            generate_button = gr.Button("Generate Image")
+
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image", interactive=False)
+
+    # Define the button click action
+    generate_button.click(
+        fn=generate_image,
+        inputs=[prompt, height, width, steps, scales, seed],
+        outputs=output_image
+    )
+
+    # Optional: Add a footer or additional information
+    gr.Markdown("© 2024 Your Name. All rights reserved.")
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+gradio-client
+
+