Update

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

.gitignore

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+### Linux ###
+*~
+
+# temporary files which can be created if a process still has a handle open of a deleted file
+.fuse_hidden*
+
+# KDE directory preferences
+.directory
+
+# Linux trash folder which might appear on any partition or disk
+.Trash-*
+
+# .nfs files are created when an open file is removed but is still being accessed
+.nfs*
+
+### OSX ###
+# General
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must end with two \r
+Icon
+
+
+# Thumbnails
+._*
+
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+### Windows ###
+# Windows thumbnail cache files
+Thumbs.db
+Thumbs.db:encryptable
+ehthumbs.db
+ehthumbs_vista.db
+
+# Dump file
+*.stackdump
+
+# Folder config file
+[Dd]esktop.ini
+
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+
+# Windows Installer files
+*.cab
+*.msi
+*.msix
+*.msm
+*.msp
+
+# Windows shortcuts
+*.lnk

README.md

@@ -1,3 +1,56 @@
-# image-embedding-pipeline-template
+# **Template: Image Embedding Pipeline**
 
-This is another test repo
+Authors:
+
+## Overview
+
+> <font color=red>**Note:** this is just a **template**, not a runnable pipeline.</font>
+
+This pipeline **cannot be run**, which is the **template for the image embedding pipeline class** and defines YAML template file for embedding images, as well as the standard inputs and outputs. You can complete the pipeline by filling in the parameters(`init_args`) of the Operator section in [image_embedding_pipeline_template.yaml](./image_embedding_pipeline_template.yaml) and update this README file. FYI, [image-embedding-resnet50](https://hub.towhee.io/towhee/image-embedding-resnet50) is based on this template.
+
+This pipeline is used to **extract the feature vector of the image**. It first normalizes the image and then uses a model to generate the vector.
+
+## Interface
+
+**Input Arguments:**
+
+- img_tensor:
+  - the input image to be encoded
+  - supported types: `PIL.Image`
+
+**Pipeline Output:**
+
+The pipeline returns a tuple `Tuple[('cnn', numpy.ndarray)]` containing following fields:
+
+- feature_vector:
+  - the embedding of input image
+  - data type: `numpy.ndarray`
+
+## How to use
+
+1. Install [Towhee](https://github.com/towhee-io/towhee)
+
+```Bash
+$ pip3 install towhee
+```
+
+> You can refer to [Getting Started with Towhee](https://towhee.io/) for more details. If you have any questions, you can [submit an issue to the towhee repository](https://github.com/towhee-io/towhee/issues).
+
+2. Run it with Towhee
+
+```Python
+>>> from towhee import pipeline
+>>> from PIL import Image
+
+>>> img = Image.open('path/to/your/image') #for example './test.jpg'
+>>> embedding_pipeline = pipeline('user/repo_name')  #the pipeline repo, such as 'towhee/image-embedding-resnet50'
+>>> embedding = embedding_pipeline(img)
+```
+
+## **How it works**
+
+This pipeline includes two main operators: [transform image](https://hub.towhee.io/towhee/transform-image-operator-template)  and [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-template). The transform image operator will first convert the original image into a normalized format, such as with 512x512 resolutions. Then, the normalized image will be encoded via image embedding operator, and finally we get a feature vector of the given image.
+
+> Refer [Towhee architecture](https://github.com/towhee-io/towhee#towhee-architecture) for basic concepts in Towhee: pipeline, operator, dataframe.
+
+![img](./readme_res/pipeline.png)

config.py

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+TEST_IMG = './test_data/test.jpg'
+DIMENSION = 1000
+REPO_NAME = 'towhee/image-embedding-resnet'

image_embedding_pipeline_template.yaml

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+name: 'image_embedding_resnet50'
+operators:
+    -
+        name: '_start_op'
+        function: '_start_op'
+        init_args:
+        inputs:
+            -
+                df: '_start_df'
+                name: 'img'
+                col: 0
+        outputs:
+            -
+                df: 'image'
+        iter_info:
+            type: map
+    -
+        name: 'preprocessing'
+        function: 'towhee/image-transform-template' #your transform-image repo name
+        tag: 'main' #tag to the repo, default is 'main'
+        init_args:
+            size:      #size of image, such as 256
+        inputs:
+            -
+                df: 'image'
+                name: 'img'
+                col: 0
+        outputs:
+            -
+                df: 'image_preproc'
+        iter_info:
+            type: map
+    -
+        name: embedding_model
+        function: 'towhee/image-embedding-operator-template' #your image-embedding repo name
+        tag: 'main' #tag to the repo, default is 'main'
+        init_args:
+            model_name:  #model_name for image-embedding operator, such as 'resnet50'
+        inputs:
+            -
+                df: 'image_preproc'
+                name: 'img_tensor'
+                col: 0
+        outputs:
+            -
+                df: 'embedding'
+        iter_info:
+            type: map
+    -
+        name: '_end_op'
+        function: '_end_op'
+        init_args:
+        inputs:
+            -
+                df: 'embedding'
+                name: 'feature_vector'
+                col: 0
+        outputs:
+            -
+                df: '_end_df'
+        iter_info:
+            type: map
+dataframes:
+    -
+        name: '_start_df'
+        columns:
+            -
+                name: 'img'
+                vtype: 'PIL.Image'
+    -
+        name: 'image'
+        columns:
+            -
+                name: 'img'
+                vtype: 'PIL.Image'
+    -
+        name: 'image_preproc'
+        columns:
+            -
+                name: 'img_transformed'
+                vtype: 'torch.Tensor'
+    -
+        name: 'embedding'
+        columns:
+            -
+                name: 'feature_vector'
+                vtype: 'numpy.ndarray'
+    -
+        name: '_end_df'
+        columns:
+            -
+                name: 'feature_vector'
+                vtype: 'numpy.ndarray'

test_image_embedding_pipeline_yaml.py

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+import unittest
+from towhee import pipeline
+from PIL import Image
+from config import DIMENSION, REPO_NAME, TEST_IMG
+
+
+class TestImageEmbeddingPipelineClass(unittest.TestCase):
+    test_img = Image.open(TEST_IMG)
+
+    def test_image_embedding_resnet50(self):
+        self.dimension = DIMENSION  #the dimension of image embedding
+        self.repo_name = REPO_NAME
+        embedding_pipeline = pipeline(self.repo_name)
+        embedding = embedding_pipeline(self.test_img)
+        assert (1, self.dimension)==op(img_tensor)[0].shape
+
+
+if __name__ == '__main__':
+    unittest.main()