Prepare FocalNet for a public repository

.github/workflows/test.yml

@@ -6,8 +6,8 @@ jobs:
   test:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v6
+      - uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262 # v4.4.0
+      - uses: astral-sh/setup-uv@d0cc045d04ccac9d8b7881df0226f9e82c39688e # v6.8.0
         with:
           enable-cache: true
       - run: uv sync --frozen --extra train
@@ -16,3 +16,17 @@ jobs:
       - run: uv run --frozen --extra train pytest -q
       - run: uv build --out-dir dist
       - run: uv run --frozen python scripts/verify-package-license.py dist
+
+  web:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: web
+    steps:
+      - uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262 # v4.4.0
+      - uses: oven-sh/setup-bun@0c5077e51419868618aeaa5fe8019c62421857d6 # v2.2.0
+        with:
+          bun-version: 1.4.2
+      - run: bun install --frozen-lockfile
+      - run: bun test
+      - run: bun run build

README.md

@@ -120,24 +120,26 @@ the same image; it is not a calibrated confidence value.
 ### Browser demo
 
 A static crop lab under `web/` runs the same format-v2 ONNX in the browser with
-ONNX Runtime Web. Photos stay on-device. The 19.45 MiB weights are gitignored;
-`bun run fetch-model` downloads them from a published artifact URL (or a local
-path / Modal volume). Bun is the package manager, bundler, test runner, and
-local static server. Publish the build with [yeet.page](https://yeet.page/):
+ONNX Runtime Web. Photos stay on-device. This repository does not publish a
+checkpoint; the 19.45 MiB weights stay gitignored. Export a model, then point
+the lab at that file. Bun is the package manager, bundler, test runner, and
+local static server:
 
 ```sh
 cd web
 bun install
-bun run fetch-model
+FOCALNET_ONNX=../artifacts/focalnet-human.onnx bun run fetch-model
 bun test
 bun run dev
-bun run build
-bunx @dittmann/yeet dist
 ```
 
-The demo compares the human-ranked crop with the importance-retention crop from
-the same map. A yeet URL is unlisted, not private: anyone with the link can
-download `focalnet-human.onnx`.
+`FOCALNET_ALLOW_DUMMY=1 bun run fetch-model` writes a tiny placeholder for UI
+layout only. Set `FOCALNET_ONNX_SHA256` to verify a known file, or
+`FOCALNET_ONNX_URL` to fetch a checkpoint you already host. Source order is
+existing `web/public/focalnet-human.onnx`, then `FOCALNET_ONNX`, then
+`FOCALNET_ONNX_URL`; dummy mode still runs if a configured URL fails. The demo
+compares the human-ranked crop with the importance-retention crop from the same
+map.
 
 ## Training
 
@@ -289,6 +291,7 @@ to other languages against this implementation.
 uv run --frozen --extra train ruff check .
 uv run --frozen --extra train ruff format --check .
 uv run --frozen --extra train pytest -q
+(cd web && bun install --frozen-lockfile && bun test)
 ```
 
 Tests cover coordinate handling, EXIF orientation, alpha composition, padding,

web/scripts/fetch-model.ts

@@ -5,12 +5,8 @@ import { join } from "node:path";
 
 const root = join(import.meta.dir, "..", "..");
 const dest = join(root, "web", "public", "focalnet-human.onnx");
-const expected =
-  Bun.env.FOCALNET_ONNX_SHA256 ??
-  "59164c601c98cea3f62b25166710831dac63e1a872fc64767c65316ad5385439";
-const modelUrl =
-  Bun.env.FOCALNET_ONNX_URL ?? "https://knowledgeable-sun-ef9f.yeet.page/focalnet-human.onnx";
-const volumePath = "/runs/repvit-m0-9-500k-cpc-gaic-lr3e4-candidate/focalnet-human.onnx";
+const expected = Bun.env.FOCALNET_ONNX_SHA256;
+const modelUrl = Bun.env.FOCALNET_ONNX_URL;
 const allowDummy = Bun.env.FOCALNET_ALLOW_DUMMY === "1";
 
 await mkdir(join(dest, ".."), { recursive: true });
@@ -24,24 +20,20 @@ async function sha256(path: string): Promise<string> {
 async function installModel(source: string): Promise<void> {
   await Bun.write(dest, Bun.file(source));
   const actual = await sha256(dest);
-  if (actual !== expected) {
+  if (expected && actual !== expected) {
     await unlink(dest);
     throw new Error(`Model hash ${actual} does not match ${expected}`);
   }
-  console.log(`Wrote ${dest}`);
+  console.log(`Wrote ${dest} (${actual})`);
 }
 
 if (await Bun.file(dest).exists()) {
   const actual = await sha256(dest);
-  if (actual === expected) {
-    console.log(`Using existing model at ${dest}`);
+  if (!expected || actual === expected || allowDummy) {
+    console.log(`Using existing model at ${dest} (${actual})`);
     process.exit(0);
   }
-  if (allowDummy) {
-    console.log(`Using existing dummy model at ${dest}`);
-    process.exit(0);
-  }
-  console.warn(`Existing model hash ${actual} does not match ${expected}; re-downloading`);
+  console.warn(`Existing model hash ${actual} does not match ${expected}; replacing`);
   await unlink(dest);
 }
 
@@ -50,40 +42,36 @@ if (Bun.env.FOCALNET_ONNX) {
   process.exit(0);
 }
 
-try {
-  const response = await fetch(modelUrl);
-  if (!response.ok) {
-    throw new Error(`GET ${modelUrl} → ${response.status}`);
-  }
+if (modelUrl) {
   const tmp = join(tmpdir(), "focalnet-human.onnx.download");
-  await Bun.write(tmp, response);
-  await installModel(tmp);
-  await unlink(tmp);
-  process.exit(0);
-} catch (error) {
-  console.warn(error instanceof Error ? error.message : error);
+  let installed = false;
+  try {
+    const response = await fetch(modelUrl);
+    if (!response.ok) {
+      throw new Error(`GET ${modelUrl} → ${response.status}`);
+    }
+    await Bun.write(tmp, response);
+    await installModel(tmp);
+    installed = true;
+  } catch (error) {
+    const detail = error instanceof Error ? error.message : String(error);
+    if (!allowDummy) {
+      throw new Error(detail);
+    }
+    console.warn(detail);
+  }
+  if (installed) {
+    await unlink(tmp).catch((error) => {
+      console.warn(error instanceof Error ? error.message : error);
+    });
+    process.exit(0);
+  }
 }
 
 if (!allowDummy) {
-  const modal = Bun.which("uvx");
-  if (modal) {
-    const tmpdirPath = join(tmpdir(), "focalnet-modal-onnx");
-    await mkdir(tmpdirPath, { recursive: true });
-    const proc = Bun.spawn(
-      ["uvx", "modal", "volume", "get", "focalnet-data", volumePath, tmpdirPath],
-      { stdout: "inherit", stderr: "inherit" },
-    );
-    if ((await proc.exited) === 0) {
-      const glob = new Bun.Glob("**/focalnet-human.onnx");
-      for await (const path of glob.scan({ cwd: tmpdirPath, absolute: true })) {
-        await installModel(path);
-        process.exit(0);
-      }
-      throw new Error(`Modal volume get did not produce ${volumePath}`);
-    }
-  }
   throw new Error(
-    `Could not fetch the production ONNX from ${modelUrl}. Set FOCALNET_ONNX or FOCALNET_ALLOW_DUMMY=1 for UI layout only.`,
+    "No local checkpoint. Export a model, then set FOCALNET_ONNX to that file " +
+      "(optional FOCALNET_ONNX_SHA256 to verify). FOCALNET_ALLOW_DUMMY=1 writes a UI placeholder.",
   );
 }
 

web/src/main.ts

@@ -65,8 +65,8 @@ app.innerHTML = `
       </aside>
     </div>
     <p class="note">
-      The ranking head is trained on CPC and GAICD judgments. This preview URL is
-      unlisted, not private: anyone with the link can download the ONNX file.
+      The ranking head is trained on CPC and GAICD judgments. This lab does not
+      ship model weights; load a local ONNX with <code>bun run fetch-model</code>.
     </p>
   </div>
 `;