Update app.py

app.py

@@ -1,154 +1,64 @@
 import gradio as gr
-import numpy as np
-import random
-
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
+from diffusers import StableDiffusionPipeline
+from PIL import Image, ImageDraw, ImageFont
 import torch
+import random
 
+# Load 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
+torch_dtype = torch.float16 if device == "cuda" else torch.float32
 
-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 = StableDiffusionPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5",
+    torch_dtype=torch_dtype,
+    revision="fp16" if device == "cuda" else None
+)
 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:
+MAX_SEED = 2**32 - 1
+
+# Add "SelamGPT" watermark to image
+def add_watermark(image):
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.load_default()
+    text = "SelamGPT"
+    margin = 10
+    x = image.width - draw.textlength(text, font=font) - margin
+    y = image.height - 20
+    draw.text((x, y), text, font=font, fill=(255, 255, 255))
+    return image
+
+# Main generation function
+def generate(prompt, seed, randomize_seed):
+    if randomize_seed or seed == 0:
         seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator(device).manual_seed(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]
-
+    image = pipe(prompt=prompt, generator=generator).images[0]
+    image = add_watermark(image)
     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",
+    "አዲስ ዘመናዊ ከተማ በደመና መካከል", 
+    "A futuristic Ethiopian skyline at night", 
+    "አንድ የፍቅር ድራማ በተራራ በታች", 
 ]
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        with gr.Row():
-            prompt = gr.Text(
-                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,
-            )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
+with gr.Blocks() as demo:
+    gr.Markdown("# SelamGPT ፡ Text-to-Image Generator 🖼️\nGenerate creative visuals from your imagination!")
 
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
+    prompt = gr.Textbox(label="Image Prompt (in Amharic or English)", placeholder="e.g. አዲስ ከተማ በጨለማ ውስጥ")
+    run_button = gr.Button("Generate")
 
-            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
-                )
+    result = gr.Image(label="Generated Image")
+    
+    with gr.Accordion("⚙️ Advanced Settings", open=False):
+        seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
+        randomize_seed = gr.Checkbox(label="🎲 Randomize seed", value=True)
 
-                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
-                )
+    gr.Examples(examples=examples, inputs=[prompt])
 
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
-    )
+    run_button.click(fn=generate, inputs=[prompt, seed, randomize_seed], outputs=[result, seed])
 
 if __name__ == "__main__":
     demo.launch()