uodate app.py

app.py

@@ -1,45 +1,27 @@
 import gradio as gr
-import subprocess
 import torch
-from PIL import Image
-from transformers import AutoProcessor, AutoModelForCausalLM
-
-
+from diffusers import StableDiffusionPipeline
+import subprocess
 
+# ติดตั้ง flash-attn เหมือนเดิม (แม้จะไม่ได้ใช้โดยตรง)
 subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-florence_model = AutoModelForCausalLM.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True).to(device).eval()
-florence_processor = AutoProcessor.from_pretrained('microsoft/Florence-2-base', trust_remote_code=True)
 
-def generate_caption(image):
-    if not isinstance(image, Image.Image):
-        image = Image.fromarray(image)
-    
-    inputs = florence_processor(text="<MORE_DETAILED_CAPTION>", images=image, return_tensors="pt").to(device)
-    generated_ids = florence_model.generate(
-        input_ids=inputs["input_ids"],
-        pixel_values=inputs["pixel_values"],
-        max_new_tokens=1024,
-        early_stopping=False,
-        do_sample=False,
-        num_beams=3,
-    )
-    generated_text = florence_processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
-    parsed_answer = florence_processor.post_process_generation(
-        generated_text,
-        task="<MORE_DETAILED_CAPTION>",
-        image_size=(image.width, image.height)
-    )
-    prompt =  parsed_answer["<MORE_DETAILED_CAPTION>"]
-    print("\n\nGeneration completed!:"+ prompt)
-    return prompt
-    
-io = gr.Interface(generate_caption,
-                  inputs=[gr.Image(label="Input Image")],
-                  outputs = [gr.Textbox(label="Output Prompt", lines=3, show_copy_button = True),
-                            ],
+# โหลดโมเดล text-to-image
+pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16 if device=="cuda" else torch.float32)
+pipe = pipe.to(device)
+pipe.safety_checker = None  # optional: remove safety checker for faster performance
+
+def generate_image(prompt):
+    result = pipe(prompt)
+    image = result.images[0]
+    return image
+
+io = gr.Interface(fn=generate_image,
+                  inputs=[gr.Textbox(label="Enter your prompt")],
+                  outputs=[gr.Image(label="Generated Image")],
                   theme="Yntec/HaleyCH_Theme_Orange",
-                  description="⚠ Sorry for the inconvenience. The space are currently running on the CPU, which might affect performance. We appreciate your understanding."
+                  description="⚠ Sorry for the inconvenience. The space is currently running on the CPU, which might affect performance. We appreciate your understanding."
                  )
 io.launch(debug=True)