Added YOLOv5 serverless function for auto labeling (#4178)

* added yolov5 serverless function for auto labeling * updated CHANGELOG.md Co-authored-by: Alex <[email protected]>
cvat-ai · Jan 17, 2022 · 182d941 · 182d941
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -29,7 +29,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added information about OpenVINO toolkit to login page (<https://github.com/openvinotoolkit/cvat/pull/4077>)
 - Support for working with ellipses (<https://github.com/openvinotoolkit/cvat/pull/4062>)
 - Add several flags to task creation CLI (<https://github.com/openvinotoolkit/cvat/pull/4119>)
-
+- Add YOLOv5 serverless function for automatic annotation (<https://github.com/openvinotoolkit/cvat/pull/4178>)
 ### Changed
 - Users don't have access to a task object anymore if they are assigneed only on some jobs of the task (<https://github.com/openvinotoolkit/cvat/pull/3788>)
 - Different resources (tasks, projects) are not visible anymore for all CVAT instance users by default (<https://github.com/openvinotoolkit/cvat/pull/3788>)

diff --git a/README.md b/README.md
@@ -90,6 +90,7 @@ For more information about supported formats look at the
 | [Object reidentification](/serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio)     | reid       | OpenVINO   | X   |     |
 | [Semantic segmentation for ADAS](/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | detector   | OpenVINO   | X   |     |
 | [Text detection v4](/serverless/openvino/omz/intel/text-detection-0004/nuclio)                          | detector   | OpenVINO   | X   |     |
+| [YOLO v5](/serverless/pytorch/ultralytics/yolov5/nuclio)                                                | detector   | PyTorch    | X   |     |
 | [SiamMask](/serverless/pytorch/foolwood/siammask/nuclio)                                                | tracker    | PyTorch    | X   | X   |
 | [f-BRS](/serverless/pytorch/saic-vul/fbrs/nuclio)                                                       | interactor | PyTorch    | X   |     |
 | [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio)                                                      | interactor | PyTorch    |     | X   |

diff --git a/serverless/pytorch/ultralytics/yolov5/nuclio/function.yaml b/serverless/pytorch/ultralytics/yolov5/nuclio/function.yaml
@@ -0,0 +1,121 @@
+metadata:
+  name: ultralytics-yolov5
+  namespace: cvat
+  annotations:
+    name: YOLO v5
+    type: detector
+    framework: pytorch
+    spec: |
+      [
+        { "id": 0, "name": "person" },
+        { "id": 1, "name": "bicycle" },
+        { "id": 2, "name": "car" },
+        { "id": 3, "name": "motorbike" },
+        { "id": 4, "name": "aeroplane" },
+        { "id": 5, "name": "bus" },
+        { "id": 6, "name": "train" },
+        { "id": 7, "name": "truck" },
+        { "id": 8, "name": "boat" },
+        { "id": 9, "name": "traffic light" },
+        { "id": 10, "name": "fire hydrant" },
+        { "id": 11, "name": "stop sign" },
+        { "id": 12, "name": "parking meter" },
+        { "id": 13, "name": "bench" },
+        { "id": 14, "name": "bird" },
+        { "id": 15, "name": "cat" },
+        { "id": 16, "name": "dog" },
+        { "id": 17, "name": "horse" },
+        { "id": 18, "name": "sheep" },
+        { "id": 19, "name": "cow" },
+        { "id": 20, "name": "elephant" },
+        { "id": 21, "name": "bear" },
+        { "id": 22, "name": "zebra" },
+        { "id": 23, "name": "giraffe" },
+        { "id": 24, "name": "backpack" },
+        { "id": 25, "name": "umbrella" },
+        { "id": 26, "name": "handbag" },
+        { "id": 27, "name": "tie" },
+        { "id": 28, "name": "suitcase" },
+        { "id": 29, "name": "frisbee" },
+        { "id": 30, "name": "skis" },
+        { "id": 31, "name": "snowboard" },
+        { "id": 32, "name": "sports ball" },
+        { "id": 33, "name": "kite" },
+        { "id": 34, "name": "baseball bat" },
+        { "id": 35, "name": "baseball glove" },
+        { "id": 36, "name": "skateboard" },
+        { "id": 37, "name": "surfboard" },
+        { "id": 38, "name": "tennis racket" },
+        { "id": 39, "name": "bottle" },
+        { "id": 40, "name": "wine glass" },
+        { "id": 41, "name": "cup" },
+        { "id": 42, "name": "fork" },
+        { "id": 43, "name": "knife" },
+        { "id": 44, "name": "spoon" },
+        { "id": 45, "name": "bowl" },
+        { "id": 46, "name": "banana" },
+        { "id": 47, "name": "apple" },
+        { "id": 48, "name": "sandwich" },
+        { "id": 49, "name": "orange" },
+        { "id": 50, "name": "broccoli" },
+        { "id": 51, "name": "carrot" },
+        { "id": 52, "name": "hot dog" },
+        { "id": 53, "name": "pizza" },
+        { "id": 54, "name": "donut" },
+        { "id": 55, "name": "cake" },
+        { "id": 56, "name": "chair" },
+        { "id": 57, "name": "sofa" },
+        { "id": 58, "name": "pottedplant" },
+        { "id": 59, "name": "bed" },
+        { "id": 60, "name": "diningtable" },
+        { "id": 61, "name": "toilet" },
+        { "id": 62, "name": "tvmonitor" },
+        { "id": 63, "name": "laptop" },
+        { "id": 64, "name": "mouse" },
+        { "id": 65, "name": "remote" },
+        { "id": 66, "name": "keyboard" },
+        { "id": 67, "name": "cell phone" },
+        { "id": 68, "name": "microwave" },
+        { "id": 69, "name": "oven" },
+        { "id": 70, "name": "toaster" },
+        { "id": 71, "name": "sink" },
+        { "id": 72, "name": "refrigerator" },
+        { "id": 73, "name": "book" },
+        { "id": 74, "name": "clock" },
+        { "id": 75, "name": "vase" },
+        { "id": 76, "name": "scissors" },
+        { "id": 77, "name": "teddy bear" },
+        { "id": 78, "name": "hair drier" },
+        { "id": 79, "name": "toothbrush" }
+      ]
+
+spec:
+  description: YOLO v5 via pytorch hub
+  runtime: 'python:3.6'
+  handler: main:handler
+  eventTimeout: 30s
+  build:
+    image: cvat/ultralytics-yolov5
+    baseImage: ultralytics/yolov5:latest
+
+    directives:
+      preCopy:
+        - kind: USER
+          value: root
+        - kind: WORKDIR
+          value: /opt/nuclio
+
+  triggers:
+    myHttpTrigger:
+      maxWorkers: 2
+      kind: 'http'
+      workerAvailabilityTimeoutMilliseconds: 10000
+      attributes:
+        maxRequestBodySize: 33554432 # 32MB
+
+  platform:
+    attributes:
+      restartPolicy:
+        name: always
+        maximumRetryCount: 3
+      mountMode: volume
diff --git a/serverless/pytorch/ultralytics/yolov5/nuclio/main.py b/serverless/pytorch/ultralytics/yolov5/nuclio/main.py
@@ -0,0 +1,40 @@
+import json
+import base64
+from PIL import Image
+import io
+import torch
+
+def init_context(context):
+    context.logger.info("Init context...  0%")
+
+    # Read the DL model
+    model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # or yolov5m, yolov5l, yolov5x, custom
+    context.user_data.model = model
+
+    context.logger.info("Init context...100%")
+
+def handler(context, event):
+    context.logger.info("Run yolo-v5 model")
+    data = event.body
+    buf = io.BytesIO(base64.b64decode(data["image"]))
+    threshold = float(data.get("threshold", 0.5))
+    context.user_data.model.conf = threshold
+    image = Image.open(buf)
+    yolo_results_json = context.user_data.model(image).pandas().xyxy[0].to_dict(orient='records')
+
+    encoded_results = []
+    for result in yolo_results_json:
+        encoded_results.append({
+            'confidence': result['confidence'],
+            'label': result['name'],
+            'points': [
+                result['xmin'],
+                result['ymin'],
+                result['xmax'],
+                result['ymax']
+            ],
+            'type': 'rectangle'
+        })
+
+    return context.Response(body=json.dumps(encoded_results), headers={},
+        content_type='application/json', status_code=200)