Rnnpool facedetection #215

oindrilasaha · 2020-11-20T21:21:45Z

added conference_room_m4 folder

harsha-simhadri

I recommend consolidating the new Conference_Room_M4 folder into the Face_Detection folder. There are many duplicated files, or files with minor differences (see below for list). There are files that add new options to existing files -- these can be folded in. The entirely new files in Conference_Room_M4 folder can be just added as is to the Face_Detection folder.

The following files are the same between the Conference_Room_M4/ and Face_Detection/ folders.

prepare_wider_data.py
requirements.txt
data/init.py
data/choose_config.py
data/ config.py
dump_model.py
layers/init.py
layers/bbox_utils.py
layers/functions/init.py
layers/functions/detection.py
layers/functions/prior_box.py
layers/modules/init.py
layers/modules/l2norm.py
layers/modules/multibox_loss.py
utils/init.py

The following files are ALMOST the same with minor edits.

Conference_Room_M4/data/config_qvga.py adds ‘_C.FACE.SCUT_DIR = '/mnt/SCUT_HEAD_Part_B'
Conference_Room_M4/data/widerface.py adds

< from data.choose_config import cfg
< cfg = cfg.cfg
18c16
< def init(self, list_file, mode='train', mono_mode=False, is_scut=False):
def __init__(self, list_file, mode='train', mono_mode=False):
< if is_scut==True:
< self.fnames.append(cfg.FACE.SCUT_DIR + '/' + line[0])
< else:
< self.fnames.append(line[0])
            self.fnames.append(line[0])

Conference_Room_M4/eval.py adds

< default='weights/rpool_face_m4.pth', help='trained model')
< parser.add_argument('--thresh', default=0.5, type=float,
                default='weights/rpool_face_c.pth', help='trained model')
parser.add_argument('--thresh', default=0.17, type=float,
< default='RPool_Face_M4', type=str,
< choices=['RPool_Face_M4'],
                default='RPool_Face_C', type=str,
                choices=['RPool_Face_C', 'RPool_Face_Quant', 'RPool_Face_QVGA_monochrome'],

Models/init.py can be consolidated to import 3 directories

The following files can be consolidated into one dir:

M4/config_qvga.py can be moved to Face_Detection/
M4/data/config_qvga.py can live inside Face_Detection/data/

harsha-simhadri · 2020-11-27T02:09:17Z

examples/pytorch/vision/Conference_Room_M4/train.py

+
+
+if __name__ == '__main__':
+    train()


newline at the end of each file

examples/pytorch/vision/Conference_Room_M4/train.py

examples/pytorch/vision/Conference_Room_M4/README.md

examples/pytorch/vision/Conference_Room_M4/evaluation.py

harsha-simhadri · 2020-11-27T02:31:01Z

pytorch/edgeml_pytorch/graph/rnn.py

@@ -182,7 +182,9 @@ def sparsify(self):
            mats[i] = utils.hardThreshold(mats[i], self._wSparsity)
        for i in range(endW, endU):
            mats[i] = utils.hardThreshold(mats[i], self._uSparsity)
-        self.copy_previous_UW()
+        self.W.data.copy_(mats[0])


have you tested that these changes do not break other rnnpool use cases?

harsha-simhadri · 2020-11-27T02:31:22Z

pytorch/edgeml_pytorch/graph/rnnpool.py

@@ -8,25 +8,32 @@

 class RNNPool(nn.Module):
    def __init__(self, nRows, nCols, nHiddenDims,
-                     nHiddenDimsBiDir, inputDims):
+                     nHiddenDimsBiDir, inputDims, 


any tests for this sparsity feature?

@oindrilasaha : any thoughts?

examples/pytorch/vision/Face_Detection/train.py

examples/pytorch/vision/Face_Detection/models/RPool_Face_C.py

examples/pytorch/vision/Conference_Room_M4/utils/augmentations.py

ShikharJ

Few minor comments, else looks good.

examples/pytorch/vision/Face_Detection/README.md

examples/pytorch/vision/Face_Detection/README_M4.md

ShikharJ · 2020-11-27T19:22:08Z

While unzipping Wider Face on Windows, I ran into File Name Too Long errors, so maybe we should document that as well for Windows users.

examples/pytorch/vision/Face_Detection/models/__init__.py

examples/pytorch/vision/Face_Detection/scut_evaluation.py

examples/pytorch/vision/Face_Detection/train.py

examples/pytorch/vision/Face_Detection/data/config_qvga.py

harsha-simhadri · 2020-11-29T20:23:01Z

examples/pytorch/vision/Face_Detection/README_M4.md

+_C.FACE.WIDER_DIR='/mnt/WIDER_FACE'.
+
+3. Run
+``` python prepare_wider_data.py ```


Failed with the following error:
(py37) harshasi@GPUnode1:~/EdgeML/examples/pytorch/vision/Face_Detection$ python3 prepare_wider_data.py
Traceback (most recent call last):
File "prepare_wider_data.py", line 10, in
from data.config import cfg
File "/home/harshasi/EdgeML/examples/pytorch/vision/Face_Detection/data/init.py", line 4, in
from .widerface import WIDERDetection
File "/home/harshasi/EdgeML/examples/pytorch/vision/Face_Detection/data/widerface.py", line 10, in
from utils.augmentations import preprocess, preprocess_qvga
File "/home/harshasi/EdgeML/examples/pytorch/vision/Face_Detection/utils/init.py", line 4, in
from .augmentations import *
File "/home/harshasi/EdgeML/examples/pytorch/vision/Face_Detection/utils/augmentations.py", line 19, in
from data.choose_config import cfg
File "/home/harshasi/EdgeML/examples/pytorch/vision/Face_Detection/data/choose_config.py", line 7, in
IS_QVGA_MONO = os.environ['IS_QVGA_MONO']
File "/home/harshasi/anaconda3/envs/py37/lib/python3.7/os.py", line 678, in getitem
raise KeyError(key) from None
KeyError: 'IS_QVGA_MONO'

have updated readme to avoid error

This should ideally be a different flag right? Because this needs to be run even when the images aren't monochrome?

ShikharJ · 2020-11-30T14:00:47Z

examples/pytorch/vision/Face_Detection/README.md

@@ -22,8 +23,12 @@ cd ..
 That is, if the WIDER_FACE folder is created in /mnt folder, then _C.HOME='/mnt'
 _C.FACE.WIDER_DIR='/mnt/WIDER_FACE'.
 Similarly, change `data/config_qvga.py` to set _C.HOME and _C.FACE.WIDER_DIR.
+For all following commands the environment variable IS_QVGA_MONO has to be set as 0 for using config.py and as 1 for using config_qvga.py as the configuration file.
+
+Note that for Windows '/' should be replaced by '\' for each path in the config files.


'\' gets cleared in the README.md. Use '\\' here please.

examples/pytorch/vision/Face_Detection/data/config_qvga.py

harsha-simhadri

Was able to follow readme_M4. Have some suggestions for improving the file. Would recommend testing by another user as well. Will review rest of files shortly.

examples/pytorch/vision/Face_Detection/README_M4.md

ShikharJ · 2020-12-23T16:07:17Z

@harsha-simhadri Can we get this merged? I need this either rebased to master or merged in for the blog.

ShikharJ · 2020-12-25T19:03:38Z

examples/pytorch/vision/Face_Detection/README.md



 ##### Dump RNNPool Input Output Traces and Weights

-To save model weights and/or input output pairs for each patch through RNNPool in numpy format use the command below. Put images which you want to save traces for in <your_image_folder> . Specify output folder for saving model weights in numpy format in <your_save_model_numpy_folder>. Specify output folder for saving input output traces of RNNPool in numpy format in <your_save_traces_numpy_folder>. Note that input traces will be saved in a folder named 'inputs' and output traces in a folder named 'outputs' inside <your_save_traces_numpy_folder>.
+For saving model weights and/or input output pairs for each patch through RNNPool in numpy format use the command below. Put images which you want to save traces for in <your_image_folder> . Specify output folder for saving model weights in numpy format in <your_save_model_numpy_folder>. Specify output folder for saving input output traces of RNNPool in numpy format in <your_save_traces_numpy_folder>. Note that input traces will be saved in a folder named 'inputs' and output traces in a folder named 'outputs' inside <your_save_traces_numpy_folder>.

 ```shell
 python3 dump_model.py --model ./weights/RPool_Face_QVGA_monochrome_best_state.pth --model_arch RPool_Face_Quant --image_folder <your_image_folder> --save_model_npy_dir <your_save_model_numpy_folder> --save_traces_npy_dir <your_save_traces_numpy_folder>


In the above command, the weight being used is RPool_Face_QVGA_monochrome_best_state.pth, but the model arch being used is RPool_Face_Quant?

@oindrilasaha I suppose this is just out of place naming, right? Or you actually using a different set of weights?

not using different weights, ill update the readme

harsha-simhadri requested changes Nov 27, 2020

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ShikharJ reviewed Nov 27, 2020

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oindrilasaha added 22 commits December 24, 2020 06:52

add m4 model

6640a8f

add rnnpool sparsity

44d98a4

revert to previous+remove basenet

7eb81bd

scut training and testing

318124d

augmentations and data file changes

ed5e15a

update readme and eval files

932efd2

evaluation code

58e4b10

fix bugs

930dfea

remove lists

2035ed8

data prep script

74c79ae

merge face detection and m4

21a0648

eval arch options

1225067

finetune

3d3b2e9

readme changes

ca69f62

readme update

7b3b8b4

readme update

62df8c6

newlines and slashes

4ef2b12

add dataset directory as environment variable

fcf4d33

rpool face c detect bug

33d28ee

support for multigpu

37e58ed

multigpu fixes

bfa6ab1

remove subset option

4b3592c

oindrilasaha added 4 commits December 24, 2020 06:52

readme edit

c964ab7

mkdir

3e04eb0

readme changes

511b60b

fix warning

86ebf13

oindrilasaha force-pushed the rnnpool-facedetection branch from 704f2bc to 86ebf13 Compare December 24, 2020 06:56

oindrilasaha added 2 commits December 24, 2020 20:13

rnnpool device

2248f94

add arch

475f0c9

ShikharJ reviewed Dec 25, 2020

View reviewed changes

trace generation

164d253

harsha-simhadri approved these changes Dec 30, 2020

View reviewed changes

harsha-simhadri and others added 7 commits January 4, 2021 13:17

Update eval.py

c3c857d

Update prior_box.py

46fbe52

Update multibox_loss.py

1185a05

Update train.py

6827e35

Update scut_test.py

0b8f773

eval bug + newlines

2e99423

Remove stray newline

c3e289a

ShikharJ force-pushed the rnnpool-facedetection branch from c87e986 to c3e289a Compare January 4, 2021 08:05

harsha-simhadri merged commit e4d5255 into master Jan 4, 2021

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Rnnpool facedetection #215

Rnnpool facedetection #215

oindrilasaha commented Nov 20, 2020

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Rnnpool facedetection #215

Rnnpool facedetection #215

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oindrilasaha commented Nov 20, 2020

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< from data.choose_config import cfg < cfg = cfg.cfg 18c16 < def init(self, list_file, mode='train', mono_mode=False, is_scut=False):

< if is_scut==True: < self.fnames.append(cfg.FACE.SCUT_DIR + '/' + line[0]) < else: < self.fnames.append(line[0])

< default='weights/rpool_face_m4.pth', help='trained model') < parser.add_argument('--thresh', default=0.5, type=float,

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< from data.choose_config import cfg
< cfg = cfg.cfg
18c16
< def init(self, list_file, mode='train', mono_mode=False, is_scut=False):

< if is_scut==True:
< self.fnames.append(cfg.FACE.SCUT_DIR + '/' + line[0])
< else:
< self.fnames.append(line[0])

< default='weights/rpool_face_m4.pth', help='trained model')
< parser.add_argument('--thresh', default=0.5, type=float,

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