Added batch processing

app.py

@@ -7,6 +7,7 @@ from PIL import Image
 import torch
 import torch.nn.functional as F
 import io
+from typing import List
 
 app = FastAPI()
 
@@ -42,3 +43,41 @@ async def classify_gender(image: UploadFile = File(...)):
         "most_likely": labels[max_idx],
         "confidence": round(probs[max_idx], 3)
     }
+
+
+
+
+@app.post("/classify_batch/")
+async def classify_gender_batch(images: List[UploadFile] = File(...)):
+    pil_images = []
+    for image in images:
+        contents = await image.read()
+        try:
+            img = Image.open(io.BytesIO(contents)).convert("RGB")
+            pil_images.append(img)
+        except Exception:
+            return {"error": f"Invalid image file: {image.filename}"}
+
+    # Batch process
+    inputs = processor(images=pil_images, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        probs = F.softmax(logits, dim=1).tolist()  # shape: [batch_size, 2]
+
+    labels = ["Female ♀", "Male ♂"]
+
+    results = []
+    for p in probs:
+        predictions = {labels[i]: round(p[i], 3) for i in range(len(p))}
+        max_idx = p.index(max(p))
+        results.append({
+            "predictions": predictions,
+            "most_likely": labels[max_idx],
+            "confidence": round(p[max_idx], 3)
+        })
+
+    return {"results": results}
+
+