@@ -1114,11 +1114,16 @@ msgstr "Не найдено моделей по этому ID"
 msgid "Voice not found."
 msgstr "Голос не найден."
 
-#: ml_model/services/FileService.py:271
+#: ml_model/services/FileService.py:293
+#, python-format
+msgid "The short side of the image must be at least %(min_side)d pixels"
+msgstr "Короткая сторона изображения должна быть не менее %(min_side)d пикселей"
+
+#: ml_model/services/FileService.py:302
 msgid "Image is too wide or tall"
 msgstr "Изображение слишком широкое или высокое"
 
-#: ml_model/services/FileService.py:279
+#: ml_model/services/FileService.py:310
 #, python-format
 msgid "The attached video must be at most %(max_seconds)d seconds"
 msgstr "Прикреплённое видео должно быть не длиннее %(max_seconds)d секунд"
@@ -274,12 +274,23 @@ class MediaFileValidator:
 
 class ImageFileValidator(MediaFileValidator):
     @staticmethod
-    def validate_dimensions(w: int | None, h: int | None, *, max_pixels: int | None) -> None:
+    def validate_dimensions(
+        w: int | None,
+        h: int | None,
+        *,
+        max_pixels: int | None = None,
+        min_side: int | None = None,
+    ) -> None:
         if not (w and h):
             raise CorruptedFileError
         if max_pixels:
             if w * h > max_pixels:
                 raise ImageTooLargeError(max_pixels)
+        if min_side and min(w, h) < min_side:
+            raise InvalidParameterError(
+                _('The short side of the image must be at least %(min_side)d pixels')
+                % {'min_side': min_side}
+            )
 
     @staticmethod
     def validate_aspect_ratio(w: int | None, h: int | None, *, min_ratio: float, max_ratio: float) -> None:
@@ -1,16 +1,15 @@
-import base64
 import time
 from datetime import timedelta
 from decimal import Decimal
 from io import BytesIO
 from typing import Any
 
-import filetype
 import requests
 from django.core.files import File
 
 from messages.models import Message
 from ml_model.exceptions import ModelVersionNotAvailable
+from ml_model.services.FileService import ImageFileProcessor, ImageFileValidator
 from ml_model.services.base import SimpleService
 from ml_model.tasks import replicate_run
 
@@ -60,12 +59,13 @@ class Hailuo(SimpleService):
             'duration': 6,
             **input_message.info,
         }
-        if input_message.file:
-            kind = filetype.guess(input_message.file.read(20))
-            mime = kind.mime if kind else 'application/octet-stream'
-            input_message.file.seek(0)
-            image = f'data:{mime};base64,{base64.b64encode(input_message.file.read()).decode("utf-8")}'
-            input_message.file.close()
+        if image := input_message.file:
+            image_processor = ImageFileProcessor(image)
+            kind = image_processor.get_kind(image_processor.get_bytes(20))
+            ImageFileValidator.validate_kind(kind, image_processor.EXTENSIONS)
+            width, height = image_processor.get_dimensions()
+            ImageFileValidator.validate_dimensions(width, height, min_side=300)
+            image.close()
             callback_data.update({'first_frame_image': image})
         start_time = time.time()
         video = replicate_run(f'minimax/{version}', callback_data)
@@ -127,6 +127,9 @@ def replicate_run(callback_url: str, payload: dict[str, Any]):
         if isinstance(image := payload.get('image'), FieldFile):
             payload['image'], temporary_file = ImageInputService.prepare_for_replicate(image)
 
+        if isinstance(image := payload.get('first_frame_image'), FieldFile):
+            payload['first_frame_image'], temporary_file = ImageInputService.prepare_for_replicate(image)
+
         output = replicate_client.run(
             ref=callback_url,
             input=payload,