get request

main.py

@@ -7,7 +7,7 @@ from typing import List
 
 import cv2
 import numpy as np
-from fastapi import FastAPI, HTTPException, UploadFile
+from fastapi import FastAPI, HTTPException, Request, UploadFile
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
 from PIL import Image
@@ -74,7 +74,8 @@ def load_dependencies():
 
 
 @app.post("/analyze/")
-async def analyze_image(image_binaries: List[UploadFile]):
+async def analyze_image(request: Request):
+    image_paths = request["image_binaries"]
     progress = print
     global trocr_pipeline
     # モデルが読み込まれているか確認
@@ -86,7 +87,7 @@ async def analyze_image(image_binaries: List[UploadFile]):
         return
 
     all_results = []
-    num_total_files = len(image_binaries)
+    num_total_files = len(image_paths)
 
     progress(0, desc="テンプレート画像読み込み中...")
     suit_templates = load_suit_templates(SUIT_TEMPLATE_PATH)
@@ -100,12 +101,12 @@ async def analyze_image(image_binaries: List[UploadFile]):
         processed_files_info = []
         # image_objects = {}
 
-        for i, image_path in enumerate(image_binaries):
+        for i, image_path in enumerate(image_paths):
             progress(
                 (i + 1) / num_total_files * 0.15,
                 desc="ステージ1/3: 文字候補を検出中...",
             )
-            filename = os.path.basename(image_path)
+            filename = os.path.basename(image_path.filename)
             progress(
                 (i + 1) / num_total_files * 0.3,
                 f"分析中 ({i+1}/{num_total_files}): {filename}",
@@ -113,12 +114,12 @@ async def analyze_image(image_binaries: List[UploadFile]):
 
             try:
                 # ファイルをバイナリモードで安全に読み込む
-                file_bytes = np.asarray(bytearray(image_path))
-                # with open(image_path, "rb") as f:
-                #     # バイトデータをNumPy配列に変換
-                #     file_bytes = np.asarray(
-                #         bytearray(f.read()), dtype=np.uint8
-                #     )
+                # file_bytes = np.asarray(bytearray(image_path))
+                with open(image_path.filename, "rb") as f:
+                    # バイトデータをNumPy配列に変換
+                    file_bytes = np.asarray(
+                        bytearray(f.read()), dtype=np.uint8
+                    )
                 # NumPy配列（メモリ上のデータ）から画像をデコード
                 image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
 
@@ -223,7 +224,7 @@ async def analyze_image(image_binaries: List[UploadFile]):
         # else:
         #     export_update = gr.update(interactive=False)
         final_result = all_results[0]["hands"]
-        filenames = [os.path.basename(p) for p in image_binaries]
+        filenames = [os.path.basename(p) for p in image_paths]
         # dropdown_update = gr.update(
         #     choices=filenames, value=filenames[0], interactive=True, open=True
         # )