ui updates.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+rayt-0.1.0-cp310-abi3-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,15 +1,16 @@
 import gradio as gr
 import io
 import sys
+import pandas as pd
 from PIL import Image
 
-from numba import cuda
-
-from rayt.camera import Camera
-from rayt.cli import random_scene
+from rayt_rust._core import Camera, Point3, Vec3
+from rayt.gpu_utils import is_cuda_available
+from rayt.scene import random_scene
 from rayt.cuda_renderer import render_with_cuda
 from rayt.numba_renderer import render_with_numba
-from rayt.vec3 import Point3, Vec3
+
+IS_CUDA_AVAILABE, _ = is_cuda_available()
 
 
 def render_image(image_width, samples_per_pixel, aspect_ratio_str, max_depth):
@@ -34,7 +35,7 @@ def render_image(image_width, samples_per_pixel, aspect_ratio_str, max_depth):
         focus_dist=10.0,
     )
 
-    if cuda.is_available():
+    if IS_CUDA_AVAILABE:
         render_func = render_with_cuda
     else:
         render_func = render_with_numba
@@ -54,13 +55,13 @@ def render_image(image_width, samples_per_pixel, aspect_ratio_str, max_depth):
 
 # --- Create the Gradio Interface ---
 with gr.Blocks() as iface:
+    gr.Markdown("# Ray Tracing in One Weekend")
+
     with gr.Row():
         with gr.Column():
-            gr.Markdown("# Ray Tracing in One Weekend")
-
             gr.Markdown("A Python implementation of the book by Peter Shirley, rendered with Numba.")
 
-            if cuda.is_available():
+            if IS_CUDA_AVAILABE:
                 gr.Markdown("CUDA support: **<span style='color: green'>AVAILABLE</span>**. Rendering will be done on the GPU.")
             else:
                 gr.Markdown(
@@ -69,18 +70,30 @@ with gr.Blocks() as iface:
                     "You can also deploy it to a server with CUDA support for faster rendering."
                 )
 
+            gr.Markdown("## PERFORMANCE")
+            gr.Markdown("Machine Configuration:")
+            gr.Markdown(
+                """
+                - **CPU:** AMD Radeon 9 9900X
+                - **GPU:** NVIDIA RTX 5080
+                """
+            )
+            dataframe = pd.DataFrame({
+                "Engine": ["Numba", "Rust", "CUDA"],
+                "Image width": ["300", "1200", "2400"],
+                "Samples per pixel": ["20", "100", "200"],
+                "Duration": ["109.38s", "231.29s", "95.31s"]
+            })
+            gr.DataFrame(dataframe)
+
+        with gr.Column():
             gr.Image(
                 label="Sample Output",
                 value="image.webp",
                 show_download_button=False,
                 show_fullscreen_button=False,
-                show_label=False,
+                show_label=True,
             )
-        with gr.Column():
-            pass
-
-        with gr.Column():
-            pass
 
     with gr.Row():
         with gr.Column():

rayt-0.1.0-cp310-abi3-linux_x86_64.whl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ae99ef6989bda524742a3004a7ed3705af562b92af2d3501cda3f01c5d6d3a0a
+size 303807

requirements.txt

@@ -1,2 +1,3 @@
 gradio
-rayt[cuda] @ git+https://github.com/gkmngrgn/rayt.git
+numba-cuda[cu13]
+./rayt-0.1.0-cp310-abi3-linux_x86_64.whl