compared with no guidance

app.py

@@ -56,16 +56,18 @@ scheduler = CommitScheduler(
     every=1
 )
 
-def save_image(prompt: str, negative_prompt: str, img_vsf: Image, img_nag: Image, parameters: dict) -> None:
+def save_image(prompt: str, negative_prompt: str, img_vsf: Image, img_nag: Image, img_normal: Image, parameters: dict) -> None:
     vsf_image_path = IMAGE_DATASET_DIR / f"{uuid4()}_vsf.png"
     nag_image_path = IMAGE_DATASET_DIR / f"{uuid4()}_nag.png"
+    normal_image_path = IMAGE_DATASET_DIR / f"{uuid4()}_normal.png"
 
     with scheduler.lock:
         img_vsf.save(vsf_image_path)
         img_nag.save(nag_image_path)
+        img_normal.save(normal_image_path)
         with IMAGE_JSONL_PATH.open("a") as f:
-            json.dump({"prompt": prompt, "negative_prompt": negative_prompt, "vsf_image_path": str(vsf_image_path), "nag_image_path": str(nag_image_path), "parameters": parameters, "timestamp": datetime.utcnow().isoformat()}, f)
-            f.write("\n")
+            json.dump({"prompt": prompt, "negative_prompt": negative_prompt, "vsf_image_path": str(vsf_image_path), "nag_image_path": str(nag_image_path), "normal_image_path": str(normal_image_path), "parameters": parameters, "timestamp": datetime.utcnow().isoformat()}, f)
+            f.write("\n") 
 
 
 pipe = pipe.to("cuda")
@@ -104,8 +106,19 @@ def generate_video(positive_prompt, negative_prompt, guidance_scale, bias, step,
     ).images[0]
     nag_path = f"images/{uuid.uuid4().hex}_nag.png"
     output_nag.save(nag_path)
+
+    output_normal = nag_pipe(
+        prompt=positive_prompt,
+        negative_prompt=negative_prompt,
+        num_inference_steps=nag_step,
+        nag_scale=0.0,
+        guidance_scale=0.0,
+    ).images[0]
+    normal_path = f"images/{uuid.uuid4().hex}_normal.png"
+    output_normal.save(normal_path)
+    
     print(f"NAG Image saved to {nag_path}")
-    save_image(positive_prompt, negative_prompt, output, output_nag, {
+    save_image(positive_prompt, negative_prompt, output, output_nag, output_normal, {
         "guidance_scale": guidance_scale,
         "bias": bias,
         "step": step,
@@ -115,7 +128,7 @@ def generate_video(positive_prompt, negative_prompt, guidance_scale, bias, step,
         "nag_tau": nag_tau,
         "nag_step": nag_step,
     })
-    return output_path, nag_path
+    return output_path, nag_path, normal_path
 
 import json
 with open("sample_prompts.json", "r") as f:
@@ -215,10 +228,10 @@ with gr.Blocks(title="Value Sign Flip SD3.5 Demo") as demo:
     with gr.Row():
         vsf_out = gr.Image(label="VSF Generated Image")
         nag_out = gr.Image(label="NAG Generated Image")
+        normal_out = gr.Image(label="Without Negative Guidance")
 
     btn = gr.Button("Generate")
-    btn.click(fn=generate_video, inputs=[pos, neg, guidance, bias, step, seed, nag_guidance, nag_alpha, nag_tau, nag_step], outputs=[vsf_out, nag_out])
-
+    btn.click(fn=generate_video, inputs=[pos, neg, guidance, bias, step, seed, nag_guidance, nag_alpha, nag_tau, nag_step], outputs=[vsf_out, nag_out, normal_out])
 
 
 demo.launch(share=True)