[fix] modify save folder

app.py

@@ -77,8 +77,8 @@ def predict(files):
                 y_offset += img.height
 
             new_img_hash = hashlib.md5(new_img.tobytes()).hexdigest()
-            if not os.path.exists(f'./pkl_files/pdf_images/{new_img_hash}.pkl'):
-                with open(f'./pkl_files/pdf_images/{new_img_hash}.pkl', 'wb') as f:
+            if not os.path.exists(f'/home/user/app/pkl_files/pdf_images/{new_img_hash}.pkl'):
+                with open(f'/home/user/app/pkl_files/pdf_images/{new_img_hash}.pkl', 'wb') as f:
                     pickle.dump(new_img, f)
 
             file_hashes.append(new_img_hash)
@@ -100,34 +100,34 @@ def predict(files):
             img_features = model.encode_image(img_batch)
 
         if request_type == 0:
-            if os.path.exists(f'./pkl_files/img_features/{new_img_hash}.pkl'):
+            if os.path.exists(f'/home/user/app/pkl_files/img_features/{new_img_hash}.pkl'):
                 continue
-            with open(f'./pkl_files/img_features/{new_img_hash}.pkl', 'wb') as f:
+            with open(f'/home/user/app/pkl_files/img_features/{new_img_hash}.pkl', 'wb') as f:
                 pickle.dump(img_features.cpu().numpy(), f)
 
     if request_type == 0:
 
         file_names_dict = dict(zip(file_hashes, file_names))
-        with open('./pkl_files/file_names.pkl', 'wb') as f:
+        with open('/home/user/app/pkl_files/file_names.pkl', 'wb') as f:
             pickle.dump(file_names_dict, f)
 
         return vis_images[0]
 
     if request_type == 1:
 
-        with open('./pkl_files/file_names.pkl', 'rb') as f:
+        with open('/home/user/app/pkl_files/file_names.pkl', 'rb') as f:
             base_file_names = pickle.load(f)
 
         base_img_hashes = []
         base_img_features = []
         base_pdf_images = {}
-        for img_file_name in os.listdir('./pkl_files/img_features'):
+        for img_file_name in os.listdir('/home/user/app/pkl_files/img_features'):
             img_hash = img_file_name.split('.')[0]
-            with open(f'./pkl_files/img_features/{img_file_name}', 'rb') as f:
+            with open(f'/home/user/app/pkl_files/img_features/{img_file_name}', 'rb') as f:
                 base_img_hashes.append(img_hash)
                 base_img_features.append(pickle.load(f))
 
-            with open(f'./pkl_files/pdf_images/{img_file_name}', 'rb') as f:
+            with open(f'/home/user/app/pkl_files/pdf_images/{img_file_name}', 'rb') as f:
                 base_pdf_images[img_hash] = pickle.load(f)
 
         base_img_features = torch.from_numpy(np.concatenate(np.array(base_img_features), axis=0)).to(device)
@@ -148,7 +148,7 @@ def predict(files):
                     print(file_name, value[i])
                     return base_pdf_images[file_hash]
                 else:
-                    return Image.open('assets/not_found.png')
+                    return Image.open('/home/user/app/assets/not_found.png')