Update app.py

app.py

@@ -1,127 +1,33 @@
 import gradio as gr
-import numpy as np
-import random
-import spaces
-import torch
-from diffusers import DiffusionPipeline
 
-dtype = torch.bfloat16
-device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = DiffusionPipeline.from_pretrained("codermert/zehra_flux", torch_dtype=dtype).to(device)
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 2048
+from infer import infer_image, infer_video
 
-@spaces.GPU()
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, num_images=4, progress=gr.Progress(track_tqdm=True)):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    
-    generator = torch.Generator().manual_seed(seed)
-    images = []
-    
-    for _ in range(num_images):
-        image = pipe(
-            prompt=prompt,
-            width=width,
-            height=height,
-            num_inference_steps=num_inference_steps,
-            generator=generator,
-            guidance_scale=0.0
-        ).images[0]
-        images.append(image)
-        # Her görsel için farklı seed kullan
-        seed = random.randint(0, MAX_SEED)
-        generator = torch.Generator().manual_seed(seed)
-    
-    return images, seed
+input_image = gr.Image(type='pil', label='Input Image')
+input_model_image = gr.Radio([('x2', 2), ('x4', 4), ('x8', 8)], type="value", value=4, label="Model Upscale/Enhance Type")
+submit_image_button = gr.Button('Submit')
+output_image = gr.Image(type="filepath", label="Output Image")
 
-examples = [
-    "a tiny astronaut hatching from an egg on the moon",
-    "a cat holding a sign that says hello world",
-    "an anime illustration of a wiener schnitzel",
-]
+tab_img = gr.Interface(
+    fn=infer_image,
+    inputs=[input_image, input_model_image],
+    outputs=output_image,
+    title="Real-ESRGAN Pytorch",
+    description="Gradio UI for Real-ESRGAN Pytorch version. To use it, simply upload your image and choose the model. Read more at the links below. Please click submit only once <br>Credits: [Nick088](https://linktr.ee/Nick088), Xinntao, Tencent, Geeve George, ai-forever, daroche <br><p style='text-align: center'><a href='https://github.com/Nick088/Real-ESRGAN_Pytorch'>Github Repo</a></p>"
+)
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 900px;
-}
-.generated-images {
-    display: grid;
-    grid-template-columns: repeat(2, 1fr);
-    gap: 10px;
-}
-"""
+input_video = gr.Video(label='Input Video')
+input_model_video = gr.Radio([('x2', 2), ('x4', 4), ('x8', 8)], type="value", value=2, label="Model Upscale/Enhance Type")
+submit_video_button = gr.Button('Submit')
+output_video = gr.Video(label='Output Video')
 
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown("""# Zehra Flux Image Generator
-        4 farklı görsel üreten AI görsel oluşturucu
-        """)
-        
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Görseliniz için prompt girin",
-                container=False,
-            )
-            run_button = gr.Button("Oluştur", scale=0)
-        
-        # 4 görsel için grid layout
-        with gr.Row(elem_classes="generated-images"):
-            results = [gr.Image(label=f"Sonuç {i+1}", show_label=True) for i in range(4)]
-        
-        with gr.Accordion("Gelişmiş Ayarlar", open=False):
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Rastgele seed", value=True)
-            
-            with gr.Row():
-                width = gr.Slider(
-                    label="Genişlik",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-                
-                height = gr.Slider(
-                    label="Yükseklik",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-            
-            num_inference_steps = gr.Slider(
-                label="Inference adım sayısı",
-                minimum=1,
-                maximum=50,
-                step=1,
-                value=4,
-            )
-        
-        gr.Examples(
-            examples=examples,
-            fn=infer,
-            inputs=[prompt],
-            outputs=[*results, 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=[*results, seed]
-    )
+tab_vid = gr.Interface(
+    fn=infer_video,
+    inputs=[input_video, input_model_video],
+    outputs=output_video,
+    title="Real-ESRGAN Pytorch",
+    description="Gradio UI for Real-ESRGAN Pytorch version. To use it, simply upload your video and choose the model. Read more at the links below. Please click submit only once <br>Credits: [Nick088](https://linktr.ee/Nick088), Xinntao, Tencent, Geeve George, ai-forever, daroche <br><p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/ai-forever/Real-ESRGAN'>Github Repo</a></p>"
+)
 
-demo.launch()
+demo = gr.TabbedInterface([tab_img, tab_vid], ["Image", "Video"])
+
+demo.launch(debug=True, show_error=True, share=True)