new

README.md

@@ -1,5 +1,5 @@
 ---
-title: Zoom and Enhance DemoFusion
+title: Enhance This DemoFusion SDXL
 emoji: 🔍🕵️
 colorFrom: blue
 colorTo: red
@@ -7,6 +7,7 @@ sdk: gradio
 sdk_version: 4.8.0
 app_file: app.py
 pinned: false
+suggested_hardware: t4-medium
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -103,7 +103,7 @@ def predict(
 
 css = """
 #intro{
-    max-width: 100%;
+    max-width: 32rem;
     text-align: center;
     margin: 0 auto;
 }
@@ -111,8 +111,16 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     gr.Markdown(
-        """# Super Resolution - SDXL
-            ## [DemoFusion](https://github.com/PRIS-CV/DemoFusion)""",
+        """
+# Zoom and Enhance with DemoFusion SDXL
+
+[DemoFusion](https://github.com/PRIS-CV/DemoFusion) enables higher-resolution image generation.  
+You can upload an initial image and prompt to generate an enhanced version. 
+[Duplicate Space](https://huggingface.co/spaces/radames/Enhance-This-DemoFusion-SDXL?duplicate=true) to avoid the queue.  
+<small>
+*Note*: The author advises against the term "super resolution" because it's more like image-to-image generation than enhancement, but it's still a lot of fun!
+</small>
+        """,
         elem_id="intro",
     )
     with gr.Row():
@@ -126,7 +134,14 @@ with gr.Blocks(css=css) as demo:
                 label="Negative Prompt",
                 value="blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
             )
-            scale = gr.Slider(minimum=2, maximum=5, value=2, step=1, label="x Scale")
+            scale = gr.Slider(
+                minimum=1,
+                maximum=5,
+                value=2,
+                step=1,
+                label="x Scale",
+                interactive=False,
+            )
             seed = gr.Slider(
                 minimum=0,
                 maximum=2**64 - 1,
@@ -140,6 +155,7 @@ with gr.Blocks(css=css) as demo:
             image_slider = ImageSlider()
             files = gr.Files()
     inputs = [image_input, prompt, negative_prompt, seed, scale]
+    # inputs = [image_input, prompt, negative_prompt, seed]
     outputs = [image_slider, files]
     btn.click(predict, inputs=inputs, outputs=outputs, concurrency_limit=1)
     gr.Examples(
@@ -149,23 +165,29 @@ with gr.Blocks(css=css) as demo:
                 "./examples/lara.jpeg",
                 "photography of lara croft 8k high definition award winning",
                 "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
-                1415926535897932,
+                1528069323235669750,
                 2,
             ],
             [
                 "./examples/cybetruck.jpeg",
                 "photo of tesla cybertruck futuristic car 8k high definition on a sand dune in mars, future",
                 "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
-                1415535897932,
-                2,
+                9257959681232992980,
+                3,
             ],
             [
                 "./examples/jesus.png",
                 "a photorealistic painting of Jesus Christ, 4k high definition",
                 "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
-                1415535897932,
+                13317204146129588000,
                 2,
             ],
+            [
+                "./examples/anna-sullivan-DioLM8ViiO8-unsplash.jpg",
+                "A crowded stadium with enthusiastic fans watching a daytime sporting event, the stands filled with colorful attire and the sun casting a warm glow"
+                "blurry, ugly, duplicate, poorly drawn, deformed, mosaic",
+                8398712905087378000,
+                3
         ],
         inputs=inputs,
         outputs=outputs,

gradio_cached_examples/14/log.csv

@@ -1,4 +0,0 @@
-component 0,component 1,flag,username,timestamp
-"[{""path"":""gradio_cached_examples/14/component 0/34ae88864c06bce42201/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null},{""path"":""gradio_cached_examples/14/component 0/6a8fb955ba369fe2bff7/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null}]","[{""path"":""gradio_cached_examples/14/component 1/ba436b05750aa6645214/img_63ac1a08-0343-4641-9a33-69f5962e3c0f_1024.jpg"",""url"":null,""size"":60364,""orig_name"":""img_63ac1a08-0343-4641-9a33-69f5962e3c0f_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/1fe673be180a2c114760/img_63ac1a08-0343-4641-9a33-69f5962e3c0f_1024.jpg"",""url"":null,""size"":60364,""orig_name"":""img_63ac1a08-0343-4641-9a33-69f5962e3c0f_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/81bcf84a09b997759a80/img_63ac1a08-0343-4641-9a33-69f5962e3c0f_2048.jpg"",""url"":null,""size"":165825,""orig_name"":""img_63ac1a08-0343-4641-9a33-69f5962e3c0f_2048.jpg"",""mime_type"":null}]",,,2023-12-06 21:13:01.073568
-"[{""path"":""gradio_cached_examples/14/component 0/c7aa01fd10d837382ac6/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null},{""path"":""gradio_cached_examples/14/component 0/e5205e81a610f8fb1fec/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null}]","[{""path"":""gradio_cached_examples/14/component 1/e65a284b320cbb3a01a4/img_f01a99d7-866a-47e1-8180-3343949327a5_1024.jpg"",""url"":null,""size"":62591,""orig_name"":""img_f01a99d7-866a-47e1-8180-3343949327a5_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/af83d83b113405a7c44e/img_f01a99d7-866a-47e1-8180-3343949327a5_1024.jpg"",""url"":null,""size"":62591,""orig_name"":""img_f01a99d7-866a-47e1-8180-3343949327a5_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/80c60ae5d95083d0bcfc/img_f01a99d7-866a-47e1-8180-3343949327a5_2048.jpg"",""url"":null,""size"":237148,""orig_name"":""img_f01a99d7-866a-47e1-8180-3343949327a5_2048.jpg"",""mime_type"":null}]",,,2023-12-06 21:14:31.614495
-"[{""path"":""gradio_cached_examples/14/component 0/e0c00f0a8f703ea49012/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null},{""path"":""gradio_cached_examples/14/component 0/8e4db924fa065750593b/image.png"",""url"":null,""size"":null,""orig_name"":null,""mime_type"":null}]","[{""path"":""gradio_cached_examples/14/component 1/2ec5e1f2c88500465499/img_85fe280c-8029-4c93-b776-4e4ed89f7a49_1024.jpg"",""url"":null,""size"":46209,""orig_name"":""img_85fe280c-8029-4c93-b776-4e4ed89f7a49_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/f7634141a2c13b47adc3/img_85fe280c-8029-4c93-b776-4e4ed89f7a49_1024.jpg"",""url"":null,""size"":46209,""orig_name"":""img_85fe280c-8029-4c93-b776-4e4ed89f7a49_1024.jpg"",""mime_type"":null},{""path"":""gradio_cached_examples/14/component 1/c3184c09057d88474a33/img_85fe280c-8029-4c93-b776-4e4ed89f7a49_2048.jpg"",""url"":null,""size"":145141,""orig_name"":""img_85fe280c-8029-4c93-b776-4e4ed89f7a49_2048.jpg"",""mime_type"":null}]",,,2023-12-06 21:16:02.149295

pipeline_demofusion_sdxl.py

@@ -16,7 +16,7 @@ import inspect
 import os
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 import matplotlib.pyplot as plt
-
+from PIL import Image
 import torch
 import torch.nn.functional as F
 import numpy as np
@@ -581,7 +581,7 @@ class DemoFusionSDXLPipeline(
         # DemoFusion specific checks
         if max(height, width) % 512 != 0:
             raise ValueError(
-                f"the larger one of `height` and `width` has to be divisible by 1024 but are {height} and {width}."
+                f"the larger one of `height` and `width` has to be divisible by 512 but are {height} and {width}."
             )
 
         if num_images_per_prompt != 1: