Shulou(Shulou.com)06/02 Report--

Editor to share with you Python how to achieve sg2im text to image, I hope you have something to gain after reading this article, let's discuss it together!

1. Download the source code from github

! git clone https://github.com/google/sg2im.git

Cloning into 'sg2im'...

Remote: Enumerating objects: 85, done. [K

Remote: Total 85 (delta 0), reused 0 (delta 0), pack-reused 85 [K]

Unpacking objects: 100% (85%), done.

! Cp-r sg2im/sg2im sg2im/scripts/

! pip install-r sg2im/requirements.txt

Collecting cloudpickle==0.5.3

Downloading https://files.pythonhosted.org/packages/e7/bf/60ae7ec1e8c6742d2abbb6819c39a48ee796793bcdb7e1d5e41a3e379ddd/cloudpickle-0.5.3-py2.py3-none-any.whl

Requirement already satisfied: cycler==0.10.0 in / usr/local/lib/python3.6/dist-packages (from-r sg2im/requirements.txt (line 2)) (0.10.0)

Collecting Cython==0.28.3

[? 25l Downloading https://files.pythonhosted.org/packages/6f/79/d8e2cd00bea8156a995fb284ce7b6677c49eccd2d318f73e201a9ce560dc/Cython-0.28.3-cp36-cp36m-manylinux1_x86_64.whl (3.4MB)

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[? 25hCollecting dask==0.17.5

[? 25l Downloading https://files.pythonhosted.org/packages/91/1a/71be14f468f8f3f94e708afd5662cf75a0ca33a78924ca9f129a9c45c66b/dask-0.17.5-py3-none-any.whl (598kB)

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[? 25hCollecting decorator==4.3.0

Downloading https://files.pythonhosted.org/packages/bc/bb/a24838832ba35baf52f32ab1a49b906b5f82fb7c76b2f6a7e35e140bac30/decorator-4.3.0-py2.py3-none-any.whl

Collecting h6py==2.8.0

[? 25l Downloading https://files.pythonhosted.org/packages/8e/cb/726134109e7bd71d98d1fcc717ffe051767aac42ede0e7326fd1787e5d64/h6py-2.8.0-cp36-cp36m-manylinux1_x86_64.whl (2.8MB)

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[? 25hCollecting imageio==2.3.0

[? 25l Downloading https://files.pythonhosted.org/packages/a7/1d/33c8686072148b3b0fcc12a2e0857dd8316b8ae20a0fa66c8d6a6d01c05c/imageio-2.3.0-py2.py3-none-any.whl (3.3MB)

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[? 25hCollecting kiwisolver==1.0.1

[? 25l Downloading https://files.pythonhosted.org/packages/69/a7/88719d132b18300b4369fbffa741841cfd36d1e637e1990f27929945b538/kiwisolver-1.0.1-cp36-cp36m-manylinux1_x86_64.whl (949kB)

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[? 25hCollecting matplotlib==2.2.2

[? 25l Downloading https://files.pythonhosted.org/packages/49/b8/89dbd27f2fb171ce753bb56220d4d4f6dbc5fe32b95d8edc4415782ef07f/matplotlib-2.2.2-cp36-cp36m-manylinux1_x86_64.whl (12.6MB)

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[? 25hCollecting networkx==2.1

[? 25l Downloading https://files.pythonhosted.org/packages/11/42/f951cc6838a4dff6ce57211c4d7f8444809ccbe2134179950301e5c4c83c/networkx-2.1.zip (1.6MB)

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[? 25hCollecting numpy==1.14.4

[? 25l Downloading https://files.pythonhosted.org/packages/4b/3d/9c0a34ad8544abef864714840fb8954d630b04433f00881bc8fde7b2ab27/numpy-1.14.4-cp36-cp36m-manylinux1_x86_64.whl (12.2MB)

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[? 25hCollecting Pillow==5.1.0

[? 25l Downloading https://files.pythonhosted.org/packages/5f/4b/8b54ab9d37b93998c81b364557dff9f61972c0f650efa0ceaf470b392740/Pillow-5.1.0-cp36-cp36m-manylinux1_x86_64.whl (2.0MB)

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[? 25hCollecting pyparsing==2.2.0

[? 25l Downloading https://files.pythonhosted.org/packages/6a/8a/718fd7d3458f9fab8e67186b00abdd345b639976bc7fb3ae722e1b026a50/pyparsing-2.2.0-py2.py3-none-any.whl (56kB)

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[? 25hCollecting python-dateutil==2.7.3

[? 25l Downloading https://files.pythonhosted.org/packages/cf/f5/af2b09c957ace60dcfac112b669c45c8c97e32f94aa8b56da4c6d1682825/python_dateutil-2.7.3-py2.py3-none-any.whl (211kB)

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[? 25hCollecting pytz==2018.4

[? 25l Downloading https://files.pythonhosted.org/packages/dc/83/15f7833b70d3e067ca91467ca245bae0f6fe56ddc7451aa0dc5606b120f2/pytz-2018.4-py2.py3-none-any.whl (510kB)

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[? 25hCollecting PyWavelets==0.5.2

[? 25l Downloading https://files.pythonhosted.org/packages/32/c0/3646053c0ce297686da524bc968bff6017151a9089d16c33afe7d330a48b/PyWavelets-0.5.2-cp36-cp36m-manylinux1_x86_64.whl (5.7MB)

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[? 25hCollecting scikit-image==0.14.0

[? 25l Downloading https://files.pythonhosted.org/packages/34/79/cefff573a53ca3fb4c390739d19541b95f371e24d2990aed4cd8837971f0/scikit_image-0.14.0-cp36-cp36m-manylinux1_x86_64.whl (25.3MB)

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[? 25hCollecting scipy==1.1.0

[? 25l Downloading https://files.pythonhosted.org/packages/a8/0b/f163da98d3a01b3e0ef1cab8dd2123c34aee2bafbb1c5bffa354cc8a1730/scipy-1.1.0-cp36-cp36m-manylinux1_x86_64.whl (31.2MB)

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[? 25hCollecting six==1.11.0

Downloading https://files.pythonhosted.org/packages/67/4b/141a581104b1f6397bfa78ac9d43d8ad29a7ca43ea90a2d863fe3056e86a/six-1.11.0-py2.py3-none-any.whl

Collecting toolz==0.9.0

[? 25l Downloading https://files.pythonhosted.org/packages/14/d0/a73c15bbeda3d2e7b381a36afb0d9cd770a9f4adc5d1532691013ba881db/toolz-0.9.0.tar.gz (45kB)

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[? 25hCollecting torch==0.4.0

[? 25l Downloading https://files.pythonhosted.org/packages/69/43/380514bd9663f1bf708abeb359b8b48d3fabb1c8e95bb3427a980a064c57/torch-0.4.0-cp36-cp36m-manylinux1_x86_64.whl (484.0MB)

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[? 25hCollecting torchvision==0.2.1

[? 25l Downloading https://files.pythonhosted.org/packages/ca/0d/f00b2885711e08bd71242ebe7b96561e6f6d01fdb4b9dcf4d37e2e13c5e1/torchvision-0.2.1-py2.py3-none-any.whl (54kB)

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25hRequirement already satisfied: setuptools in / usr/local/lib/python3.6/dist-packages (from kiwisolver==1.0.1- >-r sg2im/requirements.txt (line 8)) (47.1.1)

Building wheels for collected packages: networkx, toolz

Building wheel for networkx (setup.py)... [? 25l [? 25hdone]

Created wheel for networkx: filename=networkx-2.1-py2.py3-none-any.whl size=1447765 sha256=4e89cc8350ab7270295c4e879190531eee2b1205e4a7b0c073ed8fe950717a25

Stored in directory: / root/.cache/pip/wheels/44/c0/34/6f98693a554301bdb405f8d65d95bbcd3e50180cbfdd98a94e

Building wheel for toolz (setup.py)... [? 25l [? 25hdone]

Created wheel for toolz: filename=toolz-0.9.0-cp36-none-any.whl size=53240 sha256=eb0e9434019a90c774ffcbfb077542b8688b43df4895b0c5c57204702dadc064

Stored in directory: / root/.cache/pip/wheels/f4/0c/f6/ce6b2d1aa459ee97cc3c0f82236302bd62d89c86c700219463

Successfully built networkx toolz

[31mERROR: xarray 0.15.1 has requirement numpy > = 1.15, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: umap-learn 0.4.3 has requirement numpy > = 1.17, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: umap-learn 0.4.3 has requirement scipy > = 1.3.1, but you'll have scipy 1.1.0 which is incompatible. [0m

[31mERROR: tifffile 2020.5.30 has requirement numpy > = 1.15.1, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: tensorflow 2.2.0 has requirement h6py=2.10.0, but you'll have h6py 2.8.0 which is incompatible. [0m

[31mERROR: tensorflow 2.2.0 has requirement numpy=1.16.0, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: tensorflow 2.2.0 has requirement scipy==1.4.1; python_version > = "3", but you'll have scipy 1.1.0 which is incompatible. [0m

[31mERROR: tensorflow 2.2.0 has requirement six > = 1.12.0, but you'll have six 1.11.0 which is incompatible. [0m

[31mERROR: tensorflow-probability 0.10.0 has requirement cloudpickle > = 1.2.2, but you'll have cloudpickle 0.5.3 which is incompatible. [0m

[31mERROR: tensorflow-hub 0.8.0 has requirement six > = 1.12.0, but you'll have six 1.11.0 which is incompatible. [0m

[31mERROR: spacy 2.2.4 has requirement numpy > = 1.15.0, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: plotnine 0.6.0 has requirement matplotlib > = 3.1.1, but you'll have matplotlib 2.2.2 which is incompatible. [0m

[31mERROR: plotnine 0.6.0 has requirement numpy > = 1.16.0, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: plotnine 0.6.0 has requirement scipy > = 1.2.0, but you'll have scipy 1.1.0 which is incompatible. [0m

[31mERROR: numba 0.48.0 has requirement numpy > = 1.15, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: mizani 0.6.0 has requirement matplotlib > = 3.1.1, but you'll have matplotlib 2.2.2 which is incompatible. [0m

[31mERROR: imgaug 0.2.9 has requirement numpy > = 1.15.0, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: gym 0.17.2 has requirement cloudpickle=1.2.0, but you'll have cloudpickle 0.5.3 which is incompatible. [0m

[31mERROR: google-colab 1.0.0 has requirement six~=1.12.0, but you'll have six 1.11.0 which is incompatible. [0m

[31mERROR: featuretools 0.4.1 has requirement dask > = 0.19.4, but you'll have dask 0.17.5 which is incompatible. [0m

[31mERROR: fbprophet 0.6 has requirement python-dateutil > = 2.8.0, but you'll have python-dateutil 2.7.3 which is incompatible. [0m

[31mERROR: fastai 1.0.61 has requirement numpy > = 1.15, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: fastai 1.0.61 has requirement torch > = 1.0.0, but you'll have torch 0.4.0 which is incompatible. [0m

[31mERROR: distributed 1.25.3 has requirement dask > = 0.18.0, but you'll have dask 0.17.5 which is incompatible. [0m

[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible. [0m

[31mERROR: cvxpy 1.0.31 has requirement numpy > = 1.15, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: blis 0.4.1 has requirement numpy > = 1.15.0, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: astropy 4.0.1.post1 has requirement numpy > = 1.16, but you'll have numpy 1.14.4 which is incompatible. [0m

[31mERROR: albumentations 0.1.12 has requirement imgaug=0.2.5, but you'll have imgaug 0.2.9 which is incompatible. [0m

Installing collected packages: cloudpickle, Cython, dask, decorator, six, numpy, h6py, Pillow, imageio, kiwisolver, python-dateutil, pytz, pyparsing, matplotlib, networkx, PyWavelets, scipy, scikit-image, toolz, torch, torchvision

Found existing installation: cloudpickle 1.3.0

Uninstalling cloudpickle-1.3.0:

Successfully uninstalled cloudpickle-1.3.0

Found existing installation: Cython 0.29.19

Uninstalling Cython-0.29.19:

Successfully uninstalled Cython-0.29.19

Found existing installation: dask 2.12.0

Uninstalling dask-2.12.0:

Successfully uninstalled dask-2.12.0

Found existing installation: decorator 4.4.2

Uninstalling decorator-4.4.2:

Successfully uninstalled decorator-4.4.2

Found existing installation: six 1.12.0

Uninstalling six-1.12.0:

Successfully uninstalled six-1.12.0

Found existing installation: numpy 1.18.4

Uninstalling numpy-1.18.4:

Successfully uninstalled numpy-1.18.4

Found existing installation: h6py 2.10.0

Uninstalling h6py-2.10.0:

Successfully uninstalled h6py-2.10.0

Found existing installation: Pillow 7.0.0

Uninstalling Pillow-7.0.0:

Successfully uninstalled Pillow-7.0.0

Found existing installation: imageio 2.4.1

Uninstalling imageio-2.4.1:

Successfully uninstalled imageio-2.4.1

Found existing installation: kiwisolver 1.2.0

Uninstalling kiwisolver-1.2.0:

Successfully uninstalled kiwisolver-1.2.0

Found existing installation: python-dateutil 2.8.1

Uninstalling python-dateutil-2.8.1:

Successfully uninstalled python-dateutil-2.8.1

Found existing installation: pytz 2018.9

Uninstalling pytz-2018.9:

Successfully uninstalled pytz-2018.9

Found existing installation: pyparsing 2.4.7

Uninstalling pyparsing-2.4.7:

Successfully uninstalled pyparsing-2.4.7

Found existing installation: matplotlib 3.2.1

Uninstalling matplotlib-3.2.1:

Successfully uninstalled matplotlib-3.2.1

Found existing installation: networkx 2.4

Uninstalling networkx-2.4:

Successfully uninstalled networkx-2.4

Found existing installation: PyWavelets 1.1.1

Uninstalling PyWavelets-1.1.1:

Successfully uninstalled PyWavelets-1.1.1

Found existing installation: scipy 1.4.1

Uninstalling scipy-1.4.1:

Successfully uninstalled scipy-1.4.1

Found existing installation: scikit-image 0.16.2

Uninstalling scikit-image-0.16.2:

Successfully uninstalled scikit-image-0.16.2

Found existing installation: toolz 0.10.0

Uninstalling toolz-0.10.0:

Successfully uninstalled toolz-0.10.0

Found existing installation: torch 1.5.0+cu101

Uninstalling torch-1.5.0+cu101:

Successfully uninstalled torch-1.5.0+cu101

Found existing installation: torchvision 0.6.0+cu101

Uninstalling torchvision-0.6.0+cu101:

Successfully uninstalled torchvision-0.6.0+cu101

Successfully installed Cython-0.28.3 Pillow-5.1.0 PyWavelets-0.5.2 cloudpickle-0.5.3 dask-0.17.5 decorator-4.3.0 h6py-2.8.0 imageio-2.3.0 kiwisolver-1.0.1 matplotlib-2.2.2 networkx-2.1 numpy-1.14.4 pyparsing-2.2.0 python-dateutil-2.7.3 pytz-2018.4 scikit-image-0.14.0 scipy-1.1. 0 six-1.11.0 toolz-0.9.0 torch-0.4.0 torchvision-0.2.1

! bash sg2im/scripts/download_models.sh

-- 2020-06-05 08Fran 11RV 22rel-https://storage.googleapis.com/sg2im-data/small/coco64.pt

Resolving storage.googleapis.com (storage.googleapis.com)... 173.194.79.128, 2a00:1450:4013:c05::80

Connecting to storage.googleapis.com (storage.googleapis.com) | 173.194.79.128 |: 443. Connected.

HTTP request sent, awaiting response... 200 OK

Length: 119806264 (114m) [application/octet-stream]

Saving to: 'sg2im-models/coco64.pt'

Sg2im-models/coco64 100% [= >] 114.26M 38.5MB/s in 3.0s

2020-06-05 08:11:25 (38.5 MB/s)-'sg2im-models/coco64.pt' saved [119806264 Universe 119806264]

-- 2020-06-05 06-05 08 Fran 11RV 25muri-https://storage.googleapis.com/sg2im-data/small/vg64.pt

Resolving storage.googleapis.com (storage.googleapis.com)... 108.177.119.128, 2a00:1450:4013:c00::80

Connecting to storage.googleapis.com (storage.googleapis.com) | 108.177.119.128 |: 443. Connected.

HTTP request sent, awaiting response... 200 OK

Length: 119873465 (114m) [application/octet-stream]

Saving to: 'sg2im-models/vg64.pt'

Sg2im-models/vg64.p 100% [= >] 114.32m 44.0MB/s in 2.6s

2020-06-05 08:11:29 (44.0 MB/s)-'sg2im-models/vg64.pt' saved [119873465]

-- 2020-06-05 06-05 08 Fran 11RV 29muri-https://storage.googleapis.com/sg2im-data/small/vg128.pt

Resolving storage.googleapis.com (storage.googleapis.com)... 74.125.128.128, 2a00:1450:4013:c02::80

Connecting to storage.googleapis.com (storage.googleapis.com) | 74.125.128.128 |: 443. Connected.

HTTP request sent, awaiting response... 200 OK

Length: 129319241 (123m) [application/octet-stream]

Saving to: 'sg2im-models/vg128.pt'

Sg2im-models/vg128. [= >] 123.33m 54.2MB/s in 2.3s

2020-06-05 08:11:32 (54.2 MB/s)-'sg2im-models/vg128.pt' saved [129319241]

two。 Training and result presentation

! python3 sg2im/scripts/run_model.py-- checkpoint sg2im-models/vg128.pt-- scene_graphs sg2im/scene_graphs/figure_6_sheep.json-- output_dir outputs

Import matplotlib.pyplot as pltimport cv2%matplotlib inlineimg0 = cv2.imread ("outputs/img000000.png") img1 = cv2.imread ("outputs/img000001.png") img2 = cv2.imread ("outputs/img000002.png") img3 = cv2.imread ("outputs/img000003.png") img4 = cv2.imread ("outputs/img000004.png") img5 = cv2.imread ("outputs/img000005.png") img6 = cv2.imread ("outputs/img000006.png") plt.figure () plt.subplot (3) plt.imshow (img0) plt.subplot (3) 2) plt.imshow (img1) plt.subplot (3) plt.imshow (img2) plt.subplot (3) plt.imshow (img3) plt.subplot (3) plt.imshow (img4) plt.subplot (3) img5) plt.subplot (3) plt.imshow (img6)

! python3 sg2im/scripts/run_model.py-- checkpoint sg2im-models/vg128.pt-- scene_graphs sg2im/scene_graphs/figure_6_street.json-- output_dir outputs

Import matplotlib.pyplot as pltimport cv2%matplotlib inlineimg0 = cv2.imread ("outputs/img000000.png") img1 = cv2.imread ("outputs/img000001.png") img2 = cv2.imread ("outputs/img000002.png") img3 = cv2.imread ("outputs/img000003.png") img4 = cv2.imread ("outputs/img000004.png") img5 = cv2.imread ("outputs/img000005.png") img6 = cv2.imread ("outputs/img000006.png") plt.figure () plt.subplot (3) plt.imshow (img0) plt.subplot (3) 2) plt.imshow (img1) plt.subplot (3) plt.imshow (img2) plt.subplot (3) plt.imshow (img3) plt.subplot (3) plt.imshow (img4) plt.subplot (3) img5) plt.subplot (3) plt.imshow (img6)

! python3 sg2im/scripts/run_model.py-- checkpoint sg2im-models/vg128.pt-- scene_graphs sg2im/scene_graphs/figure_5_vg.json-- output_dir outputs

Import matplotlib.pyplot as pltimport cv2%matplotlib inlineimg0 = cv2.imread ("outputs/img000000.png") img1 = cv2.imread ("outputs/img000001.png") img2 = cv2.imread ("outputs/img000002.png") img3 = cv2.imread ("outputs/img000003.png") img4 = cv2.imread ("outputs/img000004.png") img5 = cv2.imread ("outputs/img000005.png") img6 = cv2.imread ("outputs/img000006.png") img7 = cv2.imread ("outputs/img000007.png") plt.figure () plt.subplot 1) plt.imshow (img0) plt.subplot (3penny 2) plt.imshow (img1) plt.subplot (3pence3) plt.imshow (img2) plt.subplot (3pd4) plt.imshow (img3) plt.subplot (3pint 5) plt.imshow (img4) plt.subplot (3pr 6) plt.imshow (img5) plt.subplot (3mei 3mei 7) plt.imshow (img6) plt.subplot (3pas 3je 8) plt.imshow (img7)

After reading this article, I believe you have a certain understanding of "Python how to achieve sg2im text to image". If you want to know more about it, you are welcome to follow the industry information channel. Thank you for reading!

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