Merge pull request #16 from mora-bprs/thuva

enet pages somewhat ok #14

content/docs/_index.md

@@ -2,6 +2,7 @@
 date: "2024-04-12T14:12:19+05:30"
 title: "Introduction"
 linkTitle: "Documentation"
+next: /docs/getting-started
 ---
 
 👋 Hi! Welcome!
@@ -28,17 +29,13 @@ By leveraging Mora BPRS Documentation, you'll gain a comprehensive understanding
 
 {{< callout emoji="❓" >}}
 This project is still in active development.
-Have a question or feedback? Feel free to [open an issue](https://github.com/mora-bprs/enet/issues)!
+Have a question or feedback? Feel free to [open an issue](https://github.com/mora-bprs/mora-bprs.github.io/issues)!
 {{< /callout >}}
 
-## Next
+<!-- ## Next -->
+<!---->
+<!-- Dive right into the following section to get started: -->
 
-Dive right into the following section to get started:
-
-{{< cards >}}
-{{< card link="getting-started" title="Getting Started" icon="document-text" subtitle="Learn how to create neural network models" >}}
-{{< /cards >}}
-
-[hugo]: https://gohugo.io/
-[flex-search]: https://github.com/nextapps-de/flexsearch
-[tailwind-css]: https://tailwindcss.com/
+<!-- {{< cards >}} -->
+<!-- {{< card link="getting-started" title="Getting Started" icon="document-text" subtitle="Learn how to create neural network models" >}} -->
+<!-- {{< /cards >}} -->

content/docs/models/_index.md

@@ -2,3 +2,48 @@
 date: "2024-04-12T17:39:40+05:30"
 title: "Models"
 ---
+
+![](encoderdecoder.png)
+
+## Currently being reviewed
+
+<div class="hx-mt-6">
+{{< hextra/feature-grid >}}
+{{< hextra/feature-card
+    title="SAM"
+    subtitle="Vision transformer that turns your doodles into pixel-perfect masks."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-md:hx-min-h-[340px]"
+    link="/docs/models/sam"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(194,97,254,0.15),hsla(0,0%,100%,0));">}}
+{{< hextra/feature-card
+    title="DeepLab"
+    subtitle="Atrous convolutions for multi-scale context."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-lg:hx-min-h-[340px]"
+    link="/docs/models/deeplab"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(142,53,74,0.15),hsla(0,0%,100%,0));">}}
+{{< hextra/feature-card
+    title="CornerNet"
+    subtitle="Detects objects by their crispy corner keypoints."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-md:hx-min-h-[340px]"
+    link="/docs/models/cornernet"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(221,210,59,0.15),hsla(0,0%,100%,0));">}}
+{{< hextra/feature-card
+    title="UNet"
+    subtitle="The contracting-expanding architecture that turned biomedical imaging upside down."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-md:hx-min-h-[340px]"
+    link="/docs/models/unet"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(100,97,254,0.15),hsla(0,0%,100%,0));">}}
+{{< hextra/feature-card
+    title="SegNet"
+    subtitle="The OG encoder-decoder for pixel-wise labeling way before it was cool."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-lg:hx-min-h-[340px]"
+    link="/docs/models/segnet"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(142,100,74,0.15),hsla(0,0%,100%,0));">}}
+{{< hextra/feature-card
+    title="ENet"
+    subtitle="Packs a punch on semantic segmentation without heavyweight computations."
+    class="hx-aspect-auto md:hx-aspect-[1.1/1] max-md:hx-min-h-[340px]"
+    link="/docs/models/enet"
+    style="background: radial-gradient(ellipse at 50% 80%,rgba(221,100,59,0.15),hsla(0,0%,100%,0));">}}
+{{< /hextra/feature-grid >}}
+</div>