create app.py

app.py

@@ -0,0 +1,31 @@
+from transformers import AutoProcessor, AutoModel
+import torch
+import gradio as gr
+from PIL import Image
+
+# โหลด processor และ model
+model_name = "google/siglip2-base-patch16-224"
+processor = AutoProcessor.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name)
+
+# ฟังก์ชันประมวลผล
+def match_image_text(image, text):
+    inputs = processor(text=text, images=image, return_tensors="pt", padding=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    image_embeds = outputs.image_embeds
+    text_embeds = outputs.text_embeds
+
+    # คำนวณ cosine similarity
+    similarity = torch.nn.functional.cosine_similarity(image_embeds, text_embeds).item()
+    return f"Similarity score: {similarity:.4f}"
+
+# Gradio UI
+gr.Interface(
+    fn=match_image_text,
+    inputs=[gr.Image(type="pil"), gr.Textbox(label="Enter a caption")],
+    outputs="text",
+    title="SigLIP2 Image-Text Similarity",
+    description="ใส่รูป + คำบรรยาย แล้วดูว่าโมเดลคิดว่าแมตช์กันแค่ไหน"
+).launch()