Update main.py

main.py

@@ -1,6 +1,4 @@
 import time
-total_time = time.time()
-start_time = time.time()
 
 from ultralytics import YOLO
 from base64 import b64encode
@@ -9,7 +7,6 @@ import numpy as np
 from scipy.spatial import distance as dist
 from typing import Union
 
-from sahi.utils.cv import read_image_as_pil
 from fastapi import FastAPI, File, UploadFile
 from fastapi.responses import StreamingResponse
 
@@ -20,14 +17,10 @@ from huggingface_hub import hf_hub_download
 
 from io import BytesIO
 import zipfile
-print("Import time", time.time() - start_time)
-start_time = time.time()
 
 model_path = hf_hub_download(repo_id="ultralyticsplus/yolov8s", filename='yolov8s.pt')
 model = YOLO(model_path)
 
-print("Load model time", time.time() - start_time)
-
 CLASS = model.model.names
 defaul_bot_voice = "おはいようございます"
 area_thres = 0.3
@@ -44,17 +37,18 @@ async def predict_api(
         file: UploadFile = File(...),
         last_seen: Union[UploadFile, None] = File(None)
 ):
+    total_time = time.time()
     start_time = time.time()
     image = read_image_file(await file.read())
     print("Read image", time.time() - start_time)
+    start_time = time.time()
     results = model.predict(image, show=False)[0]
-    image = read_image_as_pil(image)
+    print("Model predict", time.time() - start_time)
     masks, boxes = results.masks, results.boxes
     area_image = image.width * image.height
     most_close = 0
     out_img = None
     diff_value = 0.5
-    # total_time = time.time()
     start_time = time.time()
     if boxes is not None:
         for xyxy, conf, cls in zip(boxes.xyxy, boxes.conf, boxes.cls):
@@ -65,7 +59,7 @@ async def predict_api(
             if area_rate >= most_close:
                 out_img = image.crop(tuple(box)).resize((64, 64))
                 most_close = area_rate
-    print("Yolo time", time.time() - start_time)
+    print("Get face time", time.time() - start_time)
     start_time = time.time()
     if last_seen is not None:
         last_seen = read_image_file(await last_seen.read())