Convert more assertions / valueerrors to usererrors

daras_ai/extract_face.py

@@ -1,6 +1,10 @@
 import numpy as np
 
 
+class FaceNotFoundException(ValueError):
+    pass
+
+
 def extract_and_reposition_face_cv2(
     orig_img,
     *,
@@ -118,7 +122,7 @@ def face_oval_hull_generator(image_cv2):
         results = face_mesh.process(cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB))
 
         if not results.multi_face_landmarks:
-            raise ValueError("Face not found")
+            raise FaceNotFoundException("Face not found")
 
         for landmark_list in results.multi_face_landmarks:
             idx_to_coordinates = build_idx_to_coordinates_dict(

daras_ai_v2/asr.py

@@ -757,7 +757,7 @@ def check_wav_audio_format(filename: str) -> bool:
         data = json.loads(subprocess.check_output(args, stderr=subprocess.STDOUT))
     except subprocess.CalledProcessError as e:
         ffmpeg_output_error = ValueError(e.output, e)
-        raise ValueError(
+        raise UserError(
             "Invalid audio file. Please confirm the file is not corrupted and has a supported format (google 'ffmpeg supported audio file types')"
         ) from ffmpeg_output_error
     return (

daras_ai_v2/face_restoration.py

@@ -6,6 +6,7 @@
 import requests
 
 from daras_ai.image_input import upload_file_from_bytes
+from daras_ai_v2.exceptions import UserError
 from daras_ai_v2.gpu_server import call_gpu_server_b64, GpuEndpoints
 from daras_ai_v2.stable_diffusion import sd_upscale
 

daras_ai_v2/vector_search.py

@@ -22,6 +22,7 @@
     guess_ext_from_response,
     get_mimetype_from_response,
 )
+from daras_ai_v2.exceptions import UserError
 from daras_ai_v2 import settings
 from daras_ai_v2.asr import AsrModels, run_asr, run_google_translate
 from daras_ai_v2.azure_doc_extract import (
@@ -270,7 +271,7 @@ def doc_url_to_file_metadata(f_url: str) -> FileMetadata:
             meta = gdrive_metadata(url_to_gdrive_file_id(f))
         except HttpError as e:
             if e.status_code == 404:
-                raise FileNotFoundError(
+                raise UserError(
                     f"Could not download the google doc at {f_url} "
                     f"Please make sure to make the document public for viewing."
                 ) from e

recipes/FaceInpainting.py

@@ -6,13 +6,14 @@
 
 import gooey_ui as st
 from bots.models import Workflow
-from daras_ai.extract_face import extract_and_reposition_face_cv2
+from daras_ai.extract_face import FaceNotFoundException, extract_and_reposition_face_cv2
 from daras_ai.image_input import (
     upload_file_from_bytes,
     safe_filename,
 )
 from daras_ai_v2 import stable_diffusion
 from daras_ai_v2.base import BasePage
+from daras_ai_v2.exceptions import UserError
 from daras_ai_v2.extract_face import extract_face_img_bytes
 from daras_ai_v2.face_restoration import gfpgan
 from daras_ai_v2.functional import map_parallel
@@ -255,13 +256,16 @@ def run(self, state: dict):
         input_image_url = state["input_image"]
         img_bytes = requests.get(input_image_url).content
 
-        re_img_bytes, face_mask_bytes = extract_face_img_bytes(
-            img_bytes,
-            out_size=(state["output_width"], state["output_height"]),
-            face_scale=state["face_scale"],
-            pos_x=state["face_pos_x"],
-            pos_y=state["face_pos_y"],
-        )
+        try:
+            re_img_bytes, face_mask_bytes = extract_face_img_bytes(
+                img_bytes,
+                out_size=(state["output_width"], state["output_height"]),
+                face_scale=state["face_scale"],
+                pos_x=state["face_pos_x"],
+                pos_y=state["face_pos_y"],
+            )
+        except FaceNotFoundException as e:
+            raise UserError(str(e)) from e
 
         state["resized_image"] = upload_file_from_bytes("re_img.png", re_img_bytes)
         state["face_mask"] = upload_file_from_bytes("face_mask.png", face_mask_bytes)