remove useless lines

Dockerfile

@@ -1,6 +1,3 @@
-# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
-# you will also find guides on how best to write your Dockerfilef
-
 FROM python:3.9
 
 WORKDIR /code
@@ -9,13 +6,9 @@ COPY ./requirements.txt /code/requirements.txt
 
 RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 COPY . .
-# RUN git clone https://huggingface.co/MissingBreath/recycle-garbage-model
 
-# RUN pip install gdown
 RUN gdown 1-2xLqBeuq6ypWyPEVdfslKU1GLgD9a1_
 
-# EXPOSE 5000
-# CMD ["python", "api.py"]
 
 CMD ["uvicorn", "api:app", "--host", "0.0.0.0", "--port", "7860"]
 

api.py

@@ -1,5 +1,4 @@
 from fastapi import FastAPI, File, UploadFile
-from huggingface_hub import from_pretrained_keras
 import numpy as np
 from PIL import Image
 import io
@@ -7,8 +6,6 @@ import tensorflow as tf
 
 
 model = tf.keras.models.load_model('_9217')
-# Class labels
-# class_labels = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
 
 app = FastAPI()
 @app.post("/classify")
@@ -20,13 +17,7 @@ async def classify(image: UploadFile = File(...)):
         img_array = np.expand_dims(img_array, axis=0)
         predictions = model.predict(img_array)
         predicted_class_idx = np.argmax(predictions)
-        predicted_class_idx = int(predicted_class_idx)  
-        # predicted_class = class_labels[predicted_class_idx]
-        # return {"prediction": predicted_class}
+        predicted_class_idx = int(predicted_class_idx)
         return {"prediction": predicted_class_idx}
     else:
         return {"error": "No image provided"}
-
-# if __name__ == "__main__":
-#     import uvicorn
-#     uvicorn.run(app, host="0.0.0.0", port=8000)