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created docker #15

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6ab2205
Update .gitignore, demo.py, and 20 more files...
Nov 16, 2020
ade480f
Update README
Nov 16, 2020
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1 change: 1 addition & 0 deletions .gitignore
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/model/
9 changes: 6 additions & 3 deletions demo.py
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Expand Up @@ -12,7 +12,9 @@
from nets import txtbox_384, np_methods, txtbox_768
from processing import ssd_vgg_preprocessing

os.environ['CUDA_VISIBLE_DEVICES'] = '3' #using GPU 0
os.environ['CUDA_VISIBLE_DEVICES'] = '0' #using GPU 0
class MyError(Exception):
pass

def plt_bboxes(img, classes, scores, bboxes, figsize=(10,10), linewidth=1.5):
"""Visualize bounding boxes. Largely inspired by SSD-MXNET!
Expand Down Expand Up @@ -59,13 +61,14 @@ def plt_bboxes(img, classes, scores, bboxes, figsize=(10,10), linewidth=1.5):
with slim.arg_scope(txt_net.arg_scope(data_format=data_format)):
predictions,localisations, logits, end_points = txt_net.net(image_4d, is_training=False, reuse=reuse)

ckpt_dir = 'model'
ckpt_dir = 'model/ckpt'

isess.run(tf.global_variables_initializer())

saver = tf.train.Saver()

ckpt_filename = tf.train.latest_checkpoint(ckpt_dir)

if ckpt_dir and ckpt_filename:
print('checkpoint:',ckpt_dir, os.getcwd(), ckpt_filename)
saver.restore(isess, ckpt_filename)
Expand Down Expand Up @@ -108,5 +111,5 @@ def process_image(img, select_threshold=0.01, nms_threshold=.45, net_shape=net_s
cv2.imwrite(os.path.join(path,'demo_res.png'), img_with_bbox)
print('detection finished')
else:
raise ('no ckpt')
raise MyError('no ckpt')

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151 changes: 151 additions & 0 deletions demo/detections.txt
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[2.88985550e-01 1.89993531e-04 3.87580574e-01 1.19108364e-01
2.94231325e-01 3.90329778e-01 3.81841898e-01 2.86417544e-01
0.00000000e+00 0.00000000e+00 1.18270762e-01 1.12579495e-01],0.9995779395103455
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25 changes: 25 additions & 0 deletions docker_model/Dockerfile
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FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04

RUN apt-get update && \
apt-get install -y \
nano less tree \
python3.5 \
python3-pip \
libgl1-mesa-glx \
libglib2.0-0 \
&& \
apt-get clean && \
rm -rf /var/lib/apt/lists/*

WORKDIR /workspace
COPY requirements.txt .


RUN pip3 install --upgrade pip
RUN pip3 install -r requirements.txt

RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1
# RUN =/usr/local/cuda/lib64/stubs:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
ENV LD_LIBRARY_PATH="/usr/local/cuda/lib64/stubs:${PATH}"


20 changes: 20 additions & 0 deletions docker_model/Makefile
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IMAGE_TAG := "txpptf"

build:
docker build -t ${IMAGE_TAG} -f Dockerfile ../

run:
# Make sure directories exist to prevent permission issues
docker run \
--rm \
-v `pwd`/..:/workspace \
${IMAGE_TAG}

interactive:
# Make sure directories exist to prevent permission issues
docker run \
-it \
--rm \
-v `pwd`/..:/workspace \
${IMAGE_TAG} \
/bin/bash
2 changes: 2 additions & 0 deletions docker_model/README
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- requirements: you need to install nvidia docker from https://github.com/NVIDIA/nvidia-docker
- use `make build` to build the docker and `make interactive` to get inside and work interactively.
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17 changes: 17 additions & 0 deletions requirements.txt
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absl-py==0.11.0
astor==0.8.1
bleach==1.5.0
gast==0.4.0
grpcio==1.33.2
html5lib==0.9999999
importlib-metadata==2.0.0
Markdown==3.2.2
numpy==1.18.5
opencv-python==4.4.0.42
protobuf==3.14.0
six==1.15.0
tensorboard==1.8.0
tensorflow-gpu==1.8.0
termcolor==1.1.0
Werkzeug==1.0.1
zipp==1.2.0
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