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gradio-lite-live-zeroshot-image-classification

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whitphx HF Staff commited on Oct 29, 2023

Commit

ce16dc1

1 Parent(s): fe8f93b

Update index.html

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index.html CHANGED Viewed

@@ -1,19 +1,39 @@
 <!DOCTYPE html>
 <html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
 </html>

 <!DOCTYPE html>
 <html>
+    <head>
+        <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
+        <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
+    </head>
+    <body>
+<gradio-lite>
+<gradio-requirements>
+transformers_js_py
+</gradio-requirements>
+<gradio-file name="app.py" entrypoint>
+from transformers_js import import_transformers_js, as_url
+import gradio as gr
+transformers = await import_transformers_js()
+pipeline = transformers.pipeline
+pipe = await pipeline('zero-shot-image-classification')
+async def classify(image, classes):
+	data = await pipe(as_url(image), classes.split(","))
+	result = {item['label']: round(item['score'], 2) for item in data}
+	return result
+demo = gr.Interface(
+    classify,
+    [
+        gr.Image(label="Input image", source="webcam", type="filepath", streaming=True),
+        gr.Textbox(label="Classes separated by commas")
+    ],
+    gr.Label(),
+    live=True
+)
+demo.launch()
+</gradio-file>
+</gradio-lite>
+    </body>
 </html>