Image Download

app.py

@@ -69,9 +69,10 @@ pipe = StableDiffusionXLInstantIDPipeline.from_pretrained(
     feature_extractor=None,
 )
 #pipe.cuda()
-
-num_inference_steps = 30
-guidance_scale = 5
+if os.environ.get("MODE") == "Default":
+    print("Default")
+    num_inference_steps = 30
+    guidance_scale = 5
 
 # LCM
 if os.environ.get("MODE") == "LCM":
@@ -311,13 +312,18 @@ def generate_image(
         generator=generator,
     ).images
 
+    gradio_temp_dir = os.environ['GRADIO_TEMP_DIR']
+    temp_file_path = os.path.join(gradio_temp_dir, "image.png")
+    images[0].save(temp_file_path, format="PNG")
+    print(f"Image saved in: {temp_file_path}")
+
     gc.collect()
     if device == 'mps':
         torch.mps.empty_cache()
     elif device == 'cuda':
         torch.cuda.empty_cache()
     
-    return images[0], gr.update(visible=True)
+    return images[0], gr.update(visible=True), temp_file_path
 
 
 ### Description
@@ -363,8 +369,10 @@ tips = r"""
 """
 
 css = """
-.gradio-container {width: 85% !important}
+.gradio-container { width: 90% !important }
+#row-height { height: 65px !important }
 """
+
 with gr.Blocks(css=css) as demo:
     # description
     gr.Markdown(title)
@@ -392,7 +400,7 @@ with gr.Blocks(css=css) as demo:
 
             # strength
             identitynet_strength_ratio = gr.Slider(
-                label="IdentityNet strength (for fedility)",
+                label="IdentityNet strength (for fidelity)",
                 minimum=0,
                 maximum=1.5,
                 step=0.05,
@@ -410,7 +418,7 @@ with gr.Blocks(css=css) as demo:
                 negative_prompt = gr.Textbox(
                     label="Negative Prompt",
                     placeholder="low quality",
-                    value="(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, nudity,naked, bikini, skimpy, scanty, bare skin, lingerie, swimsuit, exposed, see-through, photo, anthropomorphic cat, monochrome, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green",
+                    value="(lowres, low quality, worst quality:1.2), (text:1.2), (frame:1.2), watermark, deformed, ugly, deformed eyes, blur, blurry, noisy, out of focus, nudity, naked, skimpy, scanty, bare skin, exposed, monochrome, pet collar",
                 )
                 num_steps = gr.Slider(
                     label="Number of sample steps",
@@ -438,6 +446,7 @@ with gr.Blocks(css=css) as demo:
 
         with gr.Column():
             output_image = gr.Image(label="Generated Image")
+            download_image = gr.File(label="Download Image", file_count="single", elem_id="row-height")
             usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
 
         submit.click(
@@ -471,13 +480,13 @@ with gr.Blocks(css=css) as demo:
                 guidance_scale,
                 seed,
             ],
-            outputs=[output_image, usage_tips],
+            outputs=[output_image, usage_tips, download_image],
         )
 
     gr.Examples(
         examples=get_example(),
         inputs=[face_file, prompt, style, negative_prompt],
-        outputs=[output_image, usage_tips],
+        outputs=[output_image, usage_tips, download_image],
         fn=run_for_examples,
     )