fix: fix bytes

main.py

@@ -1,8 +1,8 @@
 import numpy as np
 from fastapi import FastAPI, File, UploadFile
 import tensorflow as tf
-from io import StringIO
 from PIL import Image
+from io import BytesIO
 
 app = FastAPI()
 
@@ -12,23 +12,19 @@ with open("labels.txt") as f:
     for line in f:
         labels.append(line.replace('\n', ''))
 
-def classify_image(inp):
-    # Create a copy of the input array to avoid reference issues
-    inp_copy = np.copy(inp)
+def classify_image(img):
     # Resize the input image to the expected shape (224, 224)
-    inp_copy = Image.fromarray(inp_copy)
-    inp_copy = inp_copy.resize((224, 224))
-    inp_copy = np.array(inp_copy)
-    inp_copy = inp_copy.reshape((-1, 224, 224, 3))
-    inp_copy = tf.keras.applications.efficientnet.preprocess_input(inp_copy)
-    prediction = model.predict(inp_copy).flatten()
+    img_resized = img.resize((224, 224))
+    img_array = np.array(img_resized)
+    img_array = img_array.reshape((-1, 224, 224, 3))
+    img_array = tf.keras.applications.efficientnet.preprocess_input(img_array)
+    prediction = model.predict(img_array).flatten()
     confidences = {labels[i]: float(prediction[i]) for i in range(90)}
     return confidences
 
-@app.post("/predict/")
+@app.post("/predict")
 async def predict(file: UploadFile = File(...)):
     contents = await file.read()
-    img = Image.open(StringIO(contents))
-    img = np.array(img)
+    img = Image.open(BytesIO(contents))
     confidences = classify_image(img)
-    return confidences
+    return confidences