Update app.py

app.py

@@ -1,154 +1,100 @@
 import gradio as gr
-import numpy as np
-import random
-
-# import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
+import os
+import time
 
+# Konfigurasi model
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
-
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
-def infer(
-    prompt,
-    negative_prompt,
-    seed,
-    randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
-    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,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
-
-    return image, seed
-
-
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
+model_repo_id = "cagliostrolab/animagine-xl-3.1"
+
+pipe = DiffusionPipeline.from_pretrained(
+    model_repo_id, 
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32, 
+    use_safetensors=True,
+)
+pipe.to(device)
+
+# Fungsi inference
+def infer(prompt, negative_prompt, width, height, guidance_scale, num_inference_steps):
+    try:
+        # Generate image
+        image = pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            width=int(width),
+            height=int(height),
+            guidance_scale=float(guidance_scale),
+            num_inference_steps=int(num_inference_steps),
+        ).images[0]
+
+        # Simpan hasil gambar di folder output dengan nama unik berdasarkan timestamp
+        os.makedirs("./output", exist_ok=True)
+        output_path = f"./output/generated_image_{int(time.time())}.png"
+        image.save(output_path)
+
+        return image
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio interface
+with gr.Blocks() as demo:
+    # Pesan pemberitahuan jika menggunakan CPU
+    gr.Markdown(
+        "### ⚠ Sorry for the inconvenience. The Space is currently running on the CPU, which might affect performance. We appreciate your understanding."
+    )
+    
+    gr.Markdown("## Text-to-Image Generator with animagine-xl-3.1")
 
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
+    # Output gambar di atas
+    result_image = gr.Image(label="Generated Image", elem_id="result-image")
 
-        with gr.Row():
-            prompt = gr.Text(
+    # Input parameter di bawah
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(
                 label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
+                placeholder="Masukkan prompt Anda di sini",
+                value="1girl, souryuu asuka langley, neon genesis evangelion, solo, upper body, v, smile, looking at viewer, outdoors, night",
             )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt",
+                placeholder="Masukkan negative prompt untuk menghindari elemen tidak diinginkan",
+                value="nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]"
             )
 
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-            with gr.Row():
-                width = gr.Slider(
+            # Accordion untuk pengaturan lanjutan
+            with gr.Accordion("Advanced Settings", open=False):
+                width = gr.Dropdown(
                     label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    choices=["256", "512", "768", "832", "896", "1024"],
+                    value="832",
                 )
-
-                height = gr.Slider(
+                height = gr.Dropdown(
                     label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    choices=["256", "512", "768", "832", "896", "1216", "1024"],
+                    value="1216",
                 )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                guidance_scale = gr.Dropdown(
+                    label="Guidance Scale",
+                    choices=[str(i / 10) for i in range(0, 201, 10)],  # 0.0 to 20.0
+                    value="7.0",
                 )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
+                num_inference_steps = gr.Dropdown(
+                    label="Number of Inference Steps",
+                    choices=[str(i) for i in range(1, 101)],  # 1 to 100
+                    value="28",
                 )
 
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
+            run_button = gr.Button("Generate Image")
+
+    # Hubungkan fungsi infer ke UI
+    run_button.click(
         fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
+        inputs=[prompt, negative_prompt, width, height, guidance_scale, num_inference_steps],
+        outputs=result_image,
     )
 
+# Jalankan aplikasi
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()