Team Ai
Apppublic

sameersyed/Defence_FrameWork

sourceHugging Faceupdated 8mo agoView on Hugging Face
0likes
spam_detector_ml.cpython-313.pyc58 linesDownload Raw Back to __pycache__
1�

2�
i���\�SSKrSSKrSSKrSSKJr SSKrSSKJ	r	 SSK3Jr "SS5rg)�N)�Image)�MobileNetV2)�preprocess_inputc�&�\rSrSrSrSrSrSrg)�ImageSpamDetector�	c�<�[SSSS9UlSSSSS.Ulg)	N�imagenetF�avg)�weights�include_top�pooling���)�
bright_colors�
high_contrast�4small_size�
ad_dimensions)r�model�
spam_patterns)�selfs �+D:\Security_app\backend\spam_detector_ml.py�__init__�ImageSpamDetector.__init__5s+�� ���PU�V��6� ����	7���c
��SU;aURS5Sn[R"U5n[R"[8R"U55RS5nURupE[R"URS55n[R"USS9n[U5nURRUSS9SnSn/n	XE4S;aUS	-
nU	R!S95 XE-n10U11S:�dU12S:aUS
-
nU	R!S5 [R"U5n[R""U5nUS:�aUS-
nU	R!S5 [R$"U5n
U
S:�aUS-
nU	R!S5 [R&"U5nUS:aUS-
nU	R!S5 US:�aSnSnOUS	:�aSnSnOSnSn[)US5UUU	UUUR*[-[/U5S5[-[/U
5S5S .S!.$![0anS"S#[3U530sSnA$SnAff=f)$N�,��RGB)��r!r)�axis)�verbose))i��Z)i,��)i��<)�iXrzCommon ad size detected�g333333�?rzUnusual aspect ratio���z"Very bright colors (common in ads)�FzHigh contrast detectedg{�G�z�?�13zLow visual complexity�2zHIGH SPAM RISK�redzMEDIUM SPAM RISK�orangez
LOW SPAM RISK�green�d�)�width�height�format�14brightness�contrast)�15spam_score�result�color�16indicators�17image_info�errorzFailed to analyze: )�split�base64�	b64decoder�open�io�BytesIO�convert�size�np�array�resize�expand_dimsrr�predict�append�mean�std�var�minr5�round�float�	Exception�str)r�18image_data�image_bytes�imager3r4�	img_array�featuresr8r;�aspect_ratio�
img_array_rgbr6r7�feature_variancer9r:�es                  r�
analyze_image�ImageSpamDetector.analyze_images]��K	=��j� �'�-�-�c�2�1�5�19� �*�*�:�6�K��J�J�r�z�z�+�6�7�?�?��F�E�!�J�J�M�E�������j�!9�:�I����y�q�9�I�(��3�I��z�z�)�)�)�Q�)�?��B�H��J��J���"P�P��b� �20��!�!�";�<�!�>�L��a��<�#�#5��b� �21��!�!�"8�9��H�H�U�O�M�����/�J��C���b� �22��!�!�"F�G��v�v�m�,�H��"�}��b� �23��!�!�":�;� "�v�v�h�/���$�&��b� �24��!�!�"9�:��R��)�����r�!�+�� ��(����"�*�c�2� ��(�"�$�#�l�l�"'��j�(9�1�"=� %�e�H�o�q� 9���
���	=��2�3�q�6�(�;�<�<��	=�s�H-H0�025I�:I�	I�Ic�6�SU;aSUS3$SUSSUSSUSS	S26USSSUSS
SUSSSUSSS3nUS(aUSHnUSU3-
nM
 OUS-
nUS-
nUSS:�aUS-
nU$USS:�aUS-
nU$US-
nU$)Nr=zError: zY27## Image Spam Analysis Report (ML-Enhanced)28 29### Spam Risk Assessment30 31**Risk Level:** `r9z` (r8u7/100)32 33---34 35### Image Information36 37• **Dimensions:** r<r3z x r4u pixels38• **Format:** r5u39• **Brightness:** r6u/25540• **Contrast:** r7z41 42---43 44### Spam Indicators45r;u46• u 47✓ No spam indicators detectedz48 49---50 51### Recommendation52 53r-zF**High Risk:** Strong spam characteristics detected using ML analysis.rzC**Medium Risk:** Some spam characteristics detected. Verify source.z<**Low Risk:** Image appears legitimate based on ML analysis.�)r�analysis�report�	indicators    r�generate_report�!ImageSpamDetector.generate_reportdsE���h���X�g�.�/�0�0��54�8�$�%�S��,�)?�(@�A��l�+�G�4�5�S��,�9O�PX�9Y�8Z�[��,�'��1�2�3��l�+�L�9�:�;��L�)�*�5�6�7���*�L�!�%�l�3�	��F�9�+�.�.��4�
�9�9�F��5�5���L�!�R�'��^�^�F��
��l�
#�r�
)��[�[�F��
�
�T�T�F��
r)rrN)�__name__�55__module__�__qualname__�__firstlineno__rr]rd�__static_attributes__r`rrrr	s��5657�L=�\(rr)
r?rB�numpyrF�PILr�58tensorflow�tf�tensorflow.keras.applicationsr�*tensorflow.keras.applications.mobilenet_v2rrr`rr�<module>rqs&��
�	����5�G�C�Cr