forked from prehistoric-systems/comixify
d453748661
* Add frontend * Neural Image Assessment (NIMA) model * Add GPU mem fraction to NIMA model * Add backend logic * Remove whitespace * NIMA score from image array * Remove NIMA caching * Add nima model as global * NIMA model - add graph to class * Set DEBUG=True * Raise exception if NIMA model file is not found
26 lines
1.2 KiB
Python
26 lines
1.2 KiB
Python
from django.conf import settings
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from rest_framework import serializers
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from .exceptions import FileExtensionError, TooLargeFile
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class VideoSerializer(serializers.Serializer):
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file = serializers.FileField()
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frames_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_FRAMES_SAMPLING_MODE)
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rl_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_RL_MODE)
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image_assessment_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_IMAGE_ASSESSMENT_MODE)
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def validate(self, attrs):
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file = attrs.get("file")
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if file.name.split(".")[-1] not in settings.PERMITTED_VIDEO_EXTENSIONS:
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raise FileExtensionError
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if file.size > settings.MAX_FILE_SIZE:
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raise TooLargeFile
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return attrs
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class YouTubeDownloadSerializer(serializers.Serializer):
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url = serializers.URLField()
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frames_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_FRAMES_SAMPLING_MODE)
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rl_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_RL_MODE)
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image_assessment_mode = serializers.IntegerField(min_value=0, max_value=1, default=settings.DEFAULT_IMAGE_ASSESSMENT_MODE)
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