v1

app.py

@@ -0,0 +1,91 @@
+from diffusers import AutoPipelineForText2Image
+import torch
+import gradio as gr
+import threading
+import time;
+from queue import Queue
+import spaces
+
+
+@spaces.GPU(duration=120)
+def GenerateImage(prompt,steps,progress,model):
+    
+    data = []
+    
+    queue = Queue();
+    
+    def StartThread():
+        
+        pipe_txt2img = AutoPipelineForText2Image.from_pretrained(
+            model, torch_dtype=torch.float16, use_safetensors=True
+        ).to("cuda")   
+        
+        vae = pipe_txt2img.vae
+        
+        def latents_callback(i, t, latents):
+            print("Latents...");
+            latents = 1 / 0.18215 * latents
+            image = vae.decode(latents).sample[0]
+            image = (image / 2 + 0.5).clamp(0, 1)
+            image = image.cpu().permute(1, 2, 0).numpy()
+            FinalImage = pipe_txt2img.numpy_to_pil(image)
+            queue.put({'type':'image', 'image':FinalImage[0], 'step': i})
+        
+        generator = torch.Generator(device="cpu").manual_seed(37)
+        FinalImage = pipe_txt2img(prompt, generator=generator,  num_inference_steps=steps,callback=latents_callback, callback_steps=progress).images[0]
+        queue.put({'type':'image', 'image':FinalImage, 'step': steps+1})
+        queue.put({'type':'end'})
+    
+    t = threading.Thread(target=StartThread)
+    t.start();
+    
+    while True:
+        print("Waiting next item");
+        nextItem = queue.get()
+        
+        print(f"NextItem: {nextItem}");
+        
+        if nextItem['type'] == 'end':
+            break;
+                 
+        Image   = nextItem['image']
+        Step    = nextItem['step']
+        print(f"Image: {Image}")
+        yield [Image,Step];
+
+    print("Waiting thread finish...");
+    t.join()
+    
+    print("Finished!");
+
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        prompt          = gr.Text(label="Imagem prompt");
+        TotalSteps      = gr.Slider(label="Imagem prompt", minimum=1,maximum=150,value=10);
+        ProgressSteps   = gr.Number(label="Progress steps", value = 2);
+        model           = gr.Text(label="Model", value="dreamlike-art/dreamlike-photoreal-2.0")
+    
+    with gr.Row():
+        with gr.Column():
+            btnRun      = gr.Button(value="Run!");
+            btnStop   = gr.Button(value="Stop!");
+        status  = gr.Text(label="Current Step");
+   
+        
+    image   = gr.Image();
+    
+    
+    GenerateEvent = btnRun.click( GenerateImage, [prompt,TotalSteps,ProgressSteps,model], [image,status] );
+    btnStop.click( None,None,None, cancels=[GenerateEvent] )
+
+if __name__ == "__main__":
+    demo.launch(show_api=True)
+
+
+    
+
+
+
+