Merge pull request #1665 from doccano/fix/imageUpload

Fix image import

backend/data_import/celery_tasks.py

@@ -4,7 +4,7 @@ from django.contrib.auth import get_user_model
 from django.shortcuts import get_object_or_404
 
 from api.models import Project
-from .pipeline.factories import create_parser, create_bulder, create_cleaner
+from .pipeline.factories import create_parser, create_builder, create_cleaner
 from .pipeline.readers import Reader
 from .pipeline.writers import BulkWriter
 
@@ -15,7 +15,7 @@ def import_dataset(user_id, project_id, filenames, file_format: str, **kwargs):
     user = get_object_or_404(get_user_model(), pk=user_id)
 
     parser = create_parser(file_format, **kwargs)
-    builder = create_bulder(project, **kwargs)
+    builder = create_builder(project, **kwargs)
     reader = Reader(filenames=filenames, parser=parser, builder=builder)
     cleaner = create_cleaner(project)
     writer = BulkWriter(batch_size=settings.IMPORT_BATCH_SIZE)

backend/data_import/pipeline/builders.py

@@ -16,11 +16,12 @@ T = TypeVar('T')
 class PlainBuilder(Builder):
 
     def __init__(self, data_class: Type[BaseData]):
+        print(data_class)
         self.data_class = data_class
 
     def build(self, row: Dict[Any, Any], filename: str, line_num: int) -> Record:
         data = self.data_class.parse(filename=filename)
-        yield Record(data=data)
+        return Record(data=data)
 
 
 def build_label(row: Dict[Any, Any], name: str, label_class: Type[Label]) -> List[Label]:

backend/data_import/pipeline/factories.py

@@ -55,12 +55,15 @@ def create_cleaner(project):
         IMAGE_CLASSIFICATION: cleaners.CategoryCleaner
     }
     if project.project_type not in mapping:
-        ValueError(f'Invalid project type: {project.project_type}')
+        return cleaners.Cleaner(project)
     cleaner_class = mapping.get(project.project_type, cleaners.Cleaner)
     return cleaner_class(project)
 
 
-def create_bulder(project, **kwargs):
+def create_builder(project, **kwargs):
+    if not project.is_text_project:
+        return builders.PlainBuilder(data_class=get_data_class(project.project_type))
+
     data_column = builders.DataColumn(
         name=kwargs.get('column_data') or readers.DEFAULT_TEXT_COLUMN,
         value_class=get_data_class(project.project_type)

backend/data_import/pipeline/parsers.py

@@ -96,6 +96,9 @@ class PlainParser(Parser):
     This is for a task without any text.
     """
 
+    def __init__(self, **kwargs):
+        self.kwargs = kwargs
+
     def parse(self, filename: str) -> Iterator[Dict[Any, Any]]:
         yield {}
 

backend/data_import/tests/test_tasks.py

@@ -5,7 +5,7 @@ from django.test import TestCase
 from data_import.celery_tasks import import_dataset
 from api.models import (DOCUMENT_CLASSIFICATION,
                         INTENT_DETECTION_AND_SLOT_FILLING, SEQ2SEQ,
-                        SEQUENCE_LABELING)
+                        SEQUENCE_LABELING, IMAGE_CLASSIFICATION)
 from examples.models import Example
 from label_types.models import CategoryType, SpanType
 from labels.models import Category, Span
@@ -242,7 +242,7 @@ class TestImportSeq2seqData(TestImportData):
         self.assert_examples(dataset)
 
 
-class TextImportIntentDetectionAndSlotFillingData(TestImportData):
+class TestImportIntentDetectionAndSlotFillingData(TestImportData):
     task = INTENT_DETECTION_AND_SLOT_FILLING
 
     def assert_examples(self, dataset):
@@ -265,3 +265,13 @@ class TextImportIntentDetectionAndSlotFillingData(TestImportData):
         ]
         self.import_dataset(filename, file_format)
         self.assert_examples(dataset)
+
+
+class TestImportImageClassificationData(TestImportData):
+    task = IMAGE_CLASSIFICATION
+
+    def test_example(self):
+        filename = 'images/1500x500.jpeg'
+        file_format = 'ImageFile'
+        self.import_dataset(filename, file_format)
+        self.assertEqual(Example.objects.count(), 1)