Update app.py

app.py

@@ -5,11 +5,10 @@ import io
 
 app = FastAPI()
 
-# Load the lightweight zero‑shot image classification model
-# `device=-1` forces the model to run on the CPU
+# Load a compatible, lightweight zero-shot image classification model
 classifier = pipeline("zero-shot-image-classification",
-                      model="sachin/tiny_clip",
-                      device=-1)
+                      model="google/siglip2-base-patch16-224",
+                      device=-1)  # -1 forces CPU usage
 
 @app.get("/")
 def read_root():
@@ -17,20 +16,20 @@ def read_root():
 
 @app.post("/detect")
 async def detect(file: UploadFile = File(...)):
-    # 1. Read and open the uploaded image
+    # Read the uploaded image
     contents = await file.read()
     image = Image.open(io.BytesIO(contents)).convert("RGB")
 
-    # 2. Define the two possible labels for the model to choose from
+    # Define the candidate labels for the model to choose from
     candidate_labels = [
         "a photo of a fish",
         "a photo that does not contain a fish"
     ]
 
-    # 3. Run the zero‑shot classifier
+    # Perform zero-shot classification
     predictions = classifier(image, candidate_labels=candidate_labels)
 
-    # 4. The top prediction is the one with the highest score
+    # Check if the top prediction is the fish label
     if predictions[0]['label'] == "a photo of a fish":
         return "fish"
     else: