Add image-embedding-resnet50 pipeline

README.md

@@ -1,3 +1,20 @@
-# image-embedding-resnet50
+# Image Embedding Pipeline with Resnet50
 
-This is another test repo
+Authors: name or github-name(email)
+
+## Overview
+
+Introduce the functions of pipeline.
+
+## Interface
+
+The interface of pipeline.(input & output)
+
+## How to use
+
+- Requirements from requirements.txt
+- Run it with Towhee
+
+## How it works
+
+- op1->op2->op3 , and intro all the op used. (auto generate graph)

image_embedding_resnet50.yaml

@@ -0,0 +1,94 @@
+name: 'image-embedding-resnet50'
+operators:
+    -
+        name: '_start_op'
+        function: '_start_op'
+        init_args:
+        inputs:
+            -
+                df: '_start_df'
+                name: 'img_tensor'
+                col: 0
+        outputs:
+            -
+                df: 'image'
+        iter_info:
+            type: map
+    -
+        name: 'preprocessing'
+        function: 'towhee/transform-image' # same as 'transform-image', default author is towhee
+        tag: 'main' # optional
+        init_args:
+            size: 256
+        inputs:
+            -
+                df: 'image'
+                name: 'img_tensor'
+                col: 0
+        outputs:
+            -
+                df: 'image_preproc'
+        iter_info:
+            type: map
+    -
+        name: 'embedding_model'
+        function: 'towhee/resnet50-image-embedding' # same as 'resnet50-image-embedding', default user is towhee
+        tag: 'main' # optional
+        init_args:
+            model_name: 'resnet50'
+        inputs:
+            -
+                df: 'image_preproc'
+                name: 'img_tensor'
+                col: 0
+        outputs:
+            -
+                df: 'embedding'
+        iter_info:
+            type: map
+    -
+        name: '_end_op'
+        function:
+            name: '_end_op'
+        init_args:
+        inputs:
+            -
+                df: 'embedding'
+                name: 'cnn'
+                col: 0
+        outputs:
+            -
+                df: '_end_df'
+        iter_info:
+            type: map
+dataframes:
+    -
+        name: '_start_df'
+        columns:
+            -
+                name: 'img_tensor'
+                vtype: 'PIL.Image'
+    -
+        name: 'image'
+        columns:
+            -
+                name: 'img_tensor'
+                vtype: 'PIL.Image'
+    -
+        name: 'image_preproc'
+        columns:
+            -
+                name: 'img_transformed'
+                vtype: 'torch.Tensor'
+    -
+        name: 'embedding'
+        columns:
+            -
+                name: 'cnn'
+                vtype: 'numpy.ndarray'
+    -
+        name: '_end_df'
+        columns:
+            -
+                name: 'cnn'
+                vtype: 'numpy.ndarray'

test_image_embedding_resnet50.py

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+import unittest
+from towhee import pipeline
+from PIL import Image
+
+
+class TestImageEmbeddingResnet50(unittest.TestCase):
+    test_img = './test_data/test.jpg'
+    test_img = Image.open(test_img)
+
+    def test_image_embedding_resnet50(self):
+        self.dimension = 1000
+        embedding_pipeline = pipeline('towhee/image-embedding-resnet50')
+        embedding = embedding_pipeline(self.test_img)
+        assert (1, self.dimension) == op(img_tensor)[0].shape
+
+
+if __name__ == '__main__':
+    unittest.main()