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Error in importing #115

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jgdpsingh opened this issue Jun 16, 2021 · 0 comments

jgdpsingh commented Jun 16, 2021

I am getting following error on importing MTCNN class although I have installed it correctly.

from mtcnn import MTCNN
Traceback (most recent call last):

File "", line 1, in
from mtcnn import MTCNN

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn_init_.py", line 26, in
from mtcnn.mtcnn import MTCNN

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn\mtcnn.py", line 37, in
from mtcnn.network.factory import NetworkFactory

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn\network\factory.py", line 26, in
from keras.layers import Input, Dense, Conv2D, MaxPooling2D, PReLU, Flatten, Softmax

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\keras_init_.py", line 3, in
from tensorflow.keras.layers.experimental.preprocessing import RandomRotation

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow_init_.py", line 41, in
from tensorflow.python.tools import module_util as _module_util

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 45, in
from tensorflow.python import data

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data_init_.py", line 25, in
from tensorflow.python.data import experimental

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental_init_.py", line 96, in
from tensorflow.python.data.experimental import service

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\service_init_.py", line 21, in
from tensorflow.python.data.experimental.ops.data_service_ops import distribute

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py", line 25, in
from tensorflow.python.data.experimental.ops import compression_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py", line 20, in
from tensorflow.python.data.util import structure

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\util\structure.py", line 33, in
from tensorflow.python.ops import tensor_array_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\ops\tensor_array_ops.py", line 38, in
from tensorflow.python.ops import array_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1475, in
_NON_AUTOPACKABLE_TYPES = set(np.core.numerictypes.ScalarType)

AttributeError: module 'numpy.core' has no attribute 'numerictypes'

from mtcnn import MTCNN
Traceback (most recent call last):

File "", line 1, in
from mtcnn import MTCNN

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn_init_.py", line 26, in
from mtcnn.mtcnn import MTCNN

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn\mtcnn.py", line 37, in
from mtcnn.network.factory import NetworkFactory

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\mtcnn\network\factory.py", line 26, in
from keras.layers import Input, Dense, Conv2D, MaxPooling2D, PReLU, Flatten, Softmax

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\keras_init_.py", line 3, in
from tensorflow.keras.layers.experimental.preprocessing import RandomRotation

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow_init_.py", line 41, in
from tensorflow.python.tools import module_util as _module_util

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python_init_.py", line 45, in
from tensorflow.python import data

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data_init_.py", line 25, in
from tensorflow.python.data import experimental

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental_init_.py", line 96, in
from tensorflow.python.data.experimental import service

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\service_init_.py", line 21, in
from tensorflow.python.data.experimental.ops.data_service_ops import distribute

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\ops\data_service_ops.py", line 25, in
from tensorflow.python.data.experimental.ops import compression_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\experimental\ops\compression_ops.py", line 20, in
from tensorflow.python.data.util import structure

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\data\util\structure.py", line 33, in
from tensorflow.python.ops import tensor_array_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\ops\tensor_array_ops.py", line 38, in
from tensorflow.python.ops import array_ops

File "C:\Users\Jagdeep\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1475, in
_NON_AUTOPACKABLE_TYPES = set(np.core.numerictypes.ScalarType)

AttributeError: module 'numpy.core' has no attribute 'numerictypes'

ipazc pushed a commit that referenced this issue


          Refactored MTCNN codebase with significant optimizations and added ba…

1ff7228

…tch processing support

- Completely refactored the MTCNN implementation following best coding practices.
- Optimized code by removing unnecessary transpositions, resulting in faster computation. Fixes #22.
- Transposed convolutional layer weights to eliminate the need for additional transpositions during preprocessing and postprocessing, improving overall efficiency.
- Converted preprocessing and postprocessing functions into matrix operations to accelerate computation. Fixes #14, #110.
- Added batch processing support to enhance performance for multiple input images. Fixes #9, #71.
- Migrated network architecture to TensorFlow >= 2.12 for improved compatibility and performance. Fixes #80, #82, #90, #91, #93, #98, #104, #112, #114, #115, #116.
- Extensively documented the project with detailed explanations of thresholds and parameters. Fixes #12, #41, #52, #57, #99, #122, #117.
- Added support for selecting computation backends (CPU, GPU, etc.) with the `device` parameter. Fixes #23.
- Added new parameters to control the result format (support for x1, y1, x2, y2 instead of x1, y1, width, height) and the ability to return tensors instead of dictionaries. Fixes #72.
- Configured PyLint support to ensure code quality and style adherence.
- Organized functions into specific modules (`mtcnn.utils.*` and `mtcnn.stages.*`) for better modularity.
- Created Jupyter notebooks for visualization and ablation studies of each stage, allowing detailed exploration of layers, weights, and intermediate results. Fixes #88, #102.
- Added a comprehensive training guide for the model. Fixes #35, #39.
- Updated README with information on the new version, including the complete Read the Docs documentation that describes the process, theoretical background, and usage examples. Fixes #53, #73.
- Configured GitHub Actions for continuous integration and delivery (CI/CD).
- Fixed memory leak by switching to a more efficient TensorFlow method (`model(tensor)` instead of `model.predict(tensor)`). Fixes #87, #109, #121, #125, #128.
- Made TensorFlow an optional dependency to prevent conflicts with user-installed versions. Fixes #95.
- Added comprehensive unit tests for increased reliability and coverage.

ipazc mentioned this issue

MTCNN v1.0.0 #132

Closed

ipazc pushed a commit that referenced this issue


          Refactored MTCNN codebase with significant optimizations and added ba…

b6eba4b

…tch processing support

- Completely refactored the MTCNN implementation following best coding practices.
- Optimized code by removing unnecessary transpositions, resulting in faster computation. Fixes #22.
- Transposed convolutional layer weights to eliminate the need for additional transpositions during preprocessing and postprocessing, improving overall efficiency.
- Converted preprocessing and postprocessing functions into matrix operations to accelerate computation. Fixes #14, #110.
- Added batch processing support to enhance performance for multiple input images. Fixes #9, #71.
- Migrated network architecture to TensorFlow >= 2.12 for improved compatibility and performance. Fixes #80, #82, #90, #91, #93, #98, #104, #112, #114, #115, #116.
- Extensively documented the project with detailed explanations of thresholds and parameters. Fixes #12, #41, #52, #57, #99, #122, #117.
- Added support for selecting computation backends (CPU, GPU, etc.) with the `device` parameter. Fixes #23.
- Added new parameters to control the result format (support for x1, y1, x2, y2 instead of x1, y1, width, height) and the ability to return tensors instead of dictionaries. Fixes #72.
- Configured PyLint support to ensure code quality and style adherence.
- Organized functions into specific modules (`mtcnn.utils.*` and `mtcnn.stages.*`) for better modularity.
- Created Jupyter notebooks for visualization and ablation studies of each stage, allowing detailed exploration of layers, weights, and intermediate results. Fixes #88, #102.
- Added a comprehensive training guide for the model. Fixes #35, #39.
- Updated README with information on the new version, including the complete Read the Docs documentation that describes the process, theoretical background, and usage examples. Fixes #53, #73.
- Configured GitHub Actions for continuous integration and delivery (CI/CD).
- Fixed memory leak by switching to a more efficient TensorFlow method (`model(tensor)` instead of `model.predict(tensor)`). Fixes #87, #109, #121, #125, #128.
- Made TensorFlow an optional dependency to prevent conflicts with user-installed versions. Fixes #95.
- Added comprehensive unit tests for increased reliability and coverage.

ipazc mentioned this issue

Refactored MTCNN codebase with significant optimizations. Version 1.0.0 #133

Merged

ipazc closed this as completed

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