From 1ee99d169d57d819e940490b67889beb30c3b1b3 Mon Sep 17 00:00:00 2001
From: Filip Haltmayer <filip.haltmayer@zilliz.com>
Date: Thu, 10 Feb 2022 13:47:47 -0800
Subject: [PATCH] upload

---
 README.md                     |  23 ++---
 image_embedding_resnet50.yaml | 161 +++++++++++++++-------------------
 2 files changed, 77 insertions(+), 107 deletions(-)

diff --git a/README.md b/README.md
index 510e108..d8881a9 100644
--- a/README.md
+++ b/README.md
@@ -1,17 +1,17 @@
-# Pipeline: Image Embedding using Resnet50
+# Pipeline: Image Embedding using resnet50
 
-Authors: derekdqc
+Authors: Filip
 
 ## Overview
 
-The pipeline is used to **extract the feature vector of a given image**. It uses Resnet50 model to generate the vector.
+The pipeline is used to **extract the feature vector of a given image**. It uses the the resnet50 model from Ross Wightman's [`timm`](https://github.com/rwightman/pytorch-image-models) to generate the vector.
 
 ## Interface
 
 **Input Arguments:**
 
 - img_path:
-  - path to the input image
+  - the input image path
   - supported types: `str`
 
 **Pipeline Output:**
@@ -21,7 +21,8 @@ The pipeline returns a tuple `Tuple[('feature_vector', numpy.ndarray)]` containi
 - feature_vector:
   - the embedding of input image
   - data type: `numpy.ndarray`
-  - shape: (2048,)
+  - shape: (1, 2048)
+
 ## How to use
 
 1. Install [Towhee](https://github.com/towhee-io/towhee)
@@ -37,15 +38,7 @@ $ pip3 install towhee
 ```python
 >>> from towhee import pipeline
 
+>>> img_path = 'path/to/your/image'
 >>> embedding_pipeline = pipeline('towhee/image-embedding-resnet50')
->>> embedding = embedding_pipeline('path/to/your/image') #such as './readme_res/pipeline.png'
+>>> embedding = embedding_pipeline(img_path)
 ```
-
-## How it works
-
-This pipeline includes one operator: [image embedding](https://hub.towhee.io/towhee/image-embedding-operator-template) (implemented as [towhee/resnet-image-embedding](https://hub.towhee.io/towhee/resnet-image-embedding)). The image will be encoded via image embedding operator, then we can 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)
diff --git a/image_embedding_resnet50.yaml b/image_embedding_resnet50.yaml
index d201a81..9fe6a77 100644
--- a/image_embedding_resnet50.yaml
+++ b/image_embedding_resnet50.yaml
@@ -1,94 +1,71 @@
-name: 'image-embedding-resnet'
-type: 'image-embedding'
+name: image_embedding_resnet50
+type: image-embedding
 operators:
-    -
-        name: '_start_op'
-        function: '_start_op'
-        init_args:
-        inputs:
-            -
-                df: '_start_df'
-                name: 'img_path'
-                col: 0
-        outputs:
-            -
-                df: 'img_str'
-        iter_info:
-            type: map
-    -
-        name: 'image_decoder'
-        function: 'towhee/image-decoder'
-        tag: 'main'
-        init_args:
-        inputs:
-            -
-                df: 'img_str'
-                name: 'image_path'
-                col: 0
-        outputs:
-            -
-                df: 'image'
-        iter_info:
-            type: map
- 
-    -
-        name: 'embedding_model'
-        function: 'towhee/resnet-image-embedding' # same as 'resnet50-image-embedding', default user is towhee
-        tag: 'main'
-        init_args:
-            model_name: 'resnet50'
-        inputs:
-            -
-                df: 'image'
-                name: 'image'
-                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
+- name: _start_op
+  function: _start_op
+  init_args: null
+  inputs:
+  - df: _start_df
+    name: img_path
+    col: 0
+  outputs:
+  - df: img_str
+  iter_info:
+    type: map
+- name: image_decoder
+  function: towhee/image-decoder
+  tag: main
+  init_args: null
+  inputs:
+  - df: img_str
+    name: image_path
+    col: 0
+  outputs:
+  - df: image
+  iter_info:
+    type: map
+- name: embedding_model
+  function: towhee/timm-image-embedding
+  tag: main
+  init_args:
+    model_name: resnet50
+  inputs:
+  - df: image
+    name: image
+    col: 0
+  outputs:
+  - df: embedding
+  iter_info:
+    type: map
+- name: _end_op
+  function: _end_op
+  init_args: null
+  inputs:
+  - df: embedding
+    name: feature_vector
+    col: 0
+  outputs:
+  - df: _end_df
+  iter_info:
+    type: map
 dataframes:
-    -
-        name: '_start_df'
-        columns:
-            -
-                name: 'img_path'
-                vtype: 'str'
-    -
-        name: 'img_str'
-        columns:
-            -
-                name: 'img_path'
-                vtype: 'str'
-    -
-        name: 'image'
-        columns:
-            -
-                name: 'image'
-                vtype: 'towhee.types.Image'
-    -
-        name: 'embedding'
-        columns:
-            -
-                name: 'feature_vector'
-                vtype: 'numpy.ndarray'
-    -
-        name: '_end_df'
-        columns:
-            -
-                name: 'feature_vector'
-                vtype: 'numpy.ndarray'
+- name: _start_df
+  columns:
+  - name: img_path
+    vtype: str
+- name: img_str
+  columns:
+  - name: img_path
+    vtype: str
+- name: image
+  columns:
+  - name: image
+    vtype: towhee.types.Image
+- name: embedding
+  columns:
+  - name: feature_vector
+    vtype: numpy.ndarray
+- name: _end_df
+  columns:
+  - name: feature_vector
+    vtype: numpy.ndarray