Reformat folder so that they can be used in edit mode as well as use encoding to support multiple encoding

examples/python-dataflow/dataflow.yml

@@ -1,9 +1,9 @@
 nodes:
   - id: camera
-    build: pip install ../../node-hub/opencv-video-capture
+    build: pip install -e ../../node-hub/opencv-video-capture
     path: opencv-video-capture
     inputs:
-      tick: dora/timer/millis/16
+      tick: dora/timer/millis/20
     outputs:
       - image
     env:
@@ -12,7 +12,7 @@ nodes:
       IMAGE_HEIGHT: 480
 
   - id: object-detection
-    build: pip install ../../node-hub/ultralytics-yolo
+    build: pip install -e ../../node-hub/ultralytics-yolo
     path: ultralytics-yolo
     inputs:
       image:
@@ -24,7 +24,7 @@ nodes:
       MODEL: yolov8n.pt
 
   - id: plot
-    build: pip install ../../node-hub/opencv-plot
+    build: pip install -e ../../node-hub/opencv-plot
     path: opencv-plot
     inputs:
       image:

node-hub/opencv-plot/README.md

@@ -5,17 +5,17 @@ This node is used to plot a text and a list of bbox on a base image (ideal for o
 # YAML
 
 ```yaml
-  - id: opencv-plot
-    build: pip install ../../node-hub/opencv-plot
-    path: opencv-plot
-    inputs:
-      # image: Arrow array of size 1 containing the base image
-      # bbox: Arrow array of bbox
-      # text: Arrow array of size 1 containing the text to be plotted
-
-    env:
-      PLOT_WIDTH: 640 # optional, default is image input width
-      PLOT_HEIGHT: 480 # optional, default is image input height
+- id: opencv-plot
+  build: pip install ../../node-hub/opencv-plot
+  path: opencv-plot
+  inputs:
+    # image: Arrow array of size 1 containing the base image
+    # bbox: Arrow array of bbox
+    # text: Arrow array of size 1 containing the text to be plotted
+
+  env:
+    PLOT_WIDTH: 640 # optional, default is image input width
+    PLOT_HEIGHT: 480 # optional, default is image input height
 ```
 
 # Inputs
@@ -26,19 +26,18 @@ This node is used to plot a text and a list of bbox on a base image (ideal for o
 image: {
     "width": np.uint32,
     "height": np.uint32,
-    "channels": np.uint8,
+    "encoding": bytes,
     "data": np.array  # flattened image data
 }
 
 encoded_image = pa.array([image])
 
 decoded_image = {
-    "width": np.uint32(encoded_image[0]["width"].as_py()),
-    "height": np.uint32(encoded_image[0]["height"].as_py()),
-    "channels": np.uint8(encoded_image[0]["channels"].as_py()),
+    "width": np.uint32(encoded_image[0]["width"]),
+    "height": np.uint32(encoded_image[0]["height"]),
+    "encoding": encoded_image[0]["encoding"].as_py(),
     "data": encoded_image[0]["data"].values.to_numpy().astype(np.uint8)
-} 
-
+}
 ```
 
 - `bbox`: an arrow array containing the bounding boxes, confidence scores, and class names of the detected objects
@@ -68,7 +67,7 @@ text: str
 encoded_text = pa.array([text])
 
 decoded_text = encoded_text[0].as_py()
-``` 
+```
 
 ## License
 

node-hub/opencv-plot/main.py → node-hub/opencv-plot/opencv_plot/main.py

@@ -130,11 +130,20 @@ def main():
 
             if event_id == "image":
                 arrow_image = event["value"][0]
+
+                encoding = arrow_image["encoding"].as_py()
+                if encoding == "bgr8":
+                    channels = 3
+                    storage_type = np.uint8
+                else:
+                    raise Exception(f"Unsupported image encoding: {encoding}")
+
                 image = {
                     "width": np.uint32(arrow_image["width"].as_py()),
                     "height": np.uint32(arrow_image["height"].as_py()),
-                    "channels": np.uint8(arrow_image["channels"].as_py()),
-                    "data": arrow_image["data"].values.to_numpy().astype(np.uint8),
+                    "encoding": encoding,
+                    "channels": channels,
+                    "data": arrow_image["data"].values.to_numpy().astype(storage_type),
                 }
 
                 plot.frame = np.reshape(

node-hub/opencv-plot/pyproject.toml

@@ -3,14 +3,12 @@ name = "opencv-plot"
 version = "0.1"
 authors = [
     "Haixuan Xavier Tao <tao.xavier@outlook.com>",
-    "Enzo Le Van <dev@enzo-le-van.fr>"
+    "Enzo Le Van <dev@enzo-le-van.fr>",
 ]
 description = "Dora Node for plotting text and bbox on image with OpenCV"
 readme = "README.md"
 
-packages = [
-    { include = "main.py", to = "opencv_plot" }
-]
+packages = [{ include = "opencv_plot" }]
 
 [tool.poetry.dependencies]
 dora-rs = "0.3.5"
@@ -22,4 +20,4 @@ opencv-plot = "opencv_plot.main:main"
 
 [build-system]
 requires = ["poetry-core>=1.8.0"]
-build-backend = "poetry.core.masonry.api"
+build-backend = "poetry.core.masonry.api"

node-hub/opencv-video-capture/README.md

@@ -5,19 +5,19 @@ This node is used to capture video from a camera using OpenCV.
 # YAML
 
 ```yaml
-  - id: opencv-video-capture
-    build: pip install ../../node-hub/opencv-video-capture
-    path: opencv-video-capture
-    inputs:
-      tick: dora/timer/millis/16 # try to capture at 60fps
-    outputs:
-      - image: # the captured image
-
-    env:
-      PATH: 0 # optional, default is 0
-
-      IMAGE_WIDTH: 640 # optional, default is video capture width
-      IMAGE_HEIGHT: 480 # optional, default is video capture height
+- id: opencv-video-capture
+  build: pip install ../../node-hub/opencv-video-capture
+  path: opencv-video-capture
+  inputs:
+    tick: dora/timer/millis/16 # try to capture at 60fps
+  outputs:
+    - image: # the captured image
+
+  env:
+    PATH: 0 # optional, default is 0
+
+    IMAGE_WIDTH: 640 # optional, default is video capture width
+    IMAGE_HEIGHT: 480 # optional, default is video capture height
 ```
 
 # Inputs
@@ -33,16 +33,16 @@ This node is used to capture video from a camera using OpenCV.
 image: {
     "width": np.uint32,
     "height": np.uint32,
-    "channels": np.uint8,
+    "encoding": str,
     "data": np.array  # flattened image data
 }
 
 encoded_image = pa.array([image])
 
 decoded_image = {
-    "width": np.uint32(encoded_image[0]["width"].as_py()),
-    "height": np.uint32(encoded_image[0]["height"].as_py()),
-    "channels": np.uint8(encoded_image[0]["channels"].as_py()),
+    "width": np.uint32(encoded_image[0]["width"]),
+    "height": np.uint32(encoded_image[0]["height"]),
+    "encoding": encoded_image[0]["encoding"].as_py(),
     "data": encoded_image[0]["data"].values.to_numpy().astype(np.uint8)
 }
 ```

node-hub/opencv-video-capture/main.py → node-hub/opencv-video-capture/opencv_video_capture/main.py

@@ -54,18 +54,21 @@ def main():
     if isinstance(video_capture_path, str) and video_capture_path.isnumeric():
         video_capture_path = int(video_capture_path)
 
+    video_capture = cv2.VideoCapture(video_capture_path)
+
     image_width = os.getenv("IMAGE_WIDTH", args.image_width)
-    image_height = os.getenv("IMAGE_HEIGHT", args.image_height)
 
     if image_width is not None:
         if isinstance(image_width, str) and image_width.isnumeric():
             image_width = int(image_width)
+        video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, image_width)
 
+    image_height = os.getenv("IMAGE_HEIGHT", args.image_height)
     if image_height is not None:
         if isinstance(image_height, str) and image_height.isnumeric():
             image_height = int(image_height)
+        video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, image_height)
 
-    video_capture = cv2.VideoCapture(video_capture_path)
     node = Node(args.name)
     start_time = time.time()
 
@@ -105,16 +108,12 @@ def main():
                 image = {
                     "width": np.uint32(frame.shape[1]),
                     "height": np.uint32(frame.shape[0]),
-                    "channels": np.uint8(frame.shape[2]),
+                    "encoding": "bgr8",
                     "data": frame.ravel(),
                 }
 
                 node.send_output("image", pa.array([image]), event["metadata"])
 
-            if event_id == "stop":
-                video_capture.release()
-                break
-
         elif event_type == "ERROR":
             raise Exception(event["error"])
 

node-hub/opencv-video-capture/pyproject.toml

@@ -3,14 +3,12 @@ name = "opencv-video-capture"
 version = "0.1"
 authors = [
     "Haixuan Xavier Tao <tao.xavier@outlook.com>",
-    "Enzo Le Van <dev@enzo-le-van.fr>"
+    "Enzo Le Van <dev@enzo-le-van.fr>",
 ]
 description = "Dora Node for capturing video with OpenCV"
 readme = "README.md"
 
-packages = [
-    { include = "main.py", to = "opencv_video_capture" }
-]
+packages = [{ include = "opencv_video_capture" }]
 
 [tool.poetry.dependencies]
 dora-rs = "0.3.5"
@@ -22,4 +20,4 @@ opencv-video-capture = "opencv_video_capture.main:main"
 
 [build-system]
 requires = ["poetry-core>=1.8.0"]
-build-backend = "poetry.core.masonry.api"
+build-backend = "poetry.core.masonry.api"

node-hub/ultralytics-yolo/README.md

@@ -25,16 +25,16 @@ This node is used to detect objects in images using YOLOv8.
 image: {
     "width": np.uint32,
     "height": np.uint32,
-    "channels": np.uint8,
+    "encoding": str,
     "data": np.array  # flattened image data
 }
 
 encoded_image = pa.array([image])
 
 decoded_image = {
-    "width": np.uint32(encoded_image[0]["width"].as_py()),
-    "height": np.uint32(encoded_image[0]["height"].as_py()),
-    "channels": np.uint8(encoded_image[0]["channels"].as_py()),
+    "width": np.uint32(encoded_image[0]["width"]),
+    "height": np.uint32(encoded_image[0]["height"]),
+    "encoding": encoded_image[0]["encoding"].as_py(),
     "data": encoded_image[0]["data"].values.to_numpy().astype(np.uint8)
 }
 

node-hub/ultralytics-yolo/pyproject.toml

@@ -3,14 +3,12 @@ name = "ultralytics-yolo"
 version = "0.1"
 authors = [
     "Haixuan Xavier Tao <tao.xavier@outlook.com>",
-    "Enzo Le Van <dev@enzo-le-van.fr>"
+    "Enzo Le Van <dev@enzo-le-van.fr>",
 ]
 description = "Dora Node for object detection with Ultralytics YOLOv8"
 readme = "README.md"
 
-packages = [
-    { include = "main.py", to = "ultralytics_yolo" }
-]
+packages = [{ include = "ultralytics_yolo" }]
 
 [tool.poetry.dependencies]
 dora-rs = "0.3.5"
@@ -22,4 +20,4 @@ ultralytics-yolo = "ultralytics_yolo.main:main"
 
 [build-system]
 requires = ["poetry-core>=1.8.0"]
-build-backend = "poetry.core.masonry.api"
+build-backend = "poetry.core.masonry.api"

node-hub/ultralytics-yolo/main.py → node-hub/ultralytics-yolo/ultralytics_yolo/main.py

@@ -46,18 +46,29 @@ def main():
 
             if event_id == "image":
                 arrow_image = event["value"][0]
+                encoding = arrow_image["encoding"].as_py()
+
+                if encoding == "bgr8":
+                    channels = 3
+                    storage_type = np.uint8
+                else:
+                    raise Exception(f"Unsupported image encoding: {encoding}")
+
                 image = {
                     "width": np.uint32(arrow_image["width"].as_py()),
                     "height": np.uint32(arrow_image["height"].as_py()),
-                    "channels": np.uint8(arrow_image["channels"].as_py()),
-                    "data": arrow_image["data"].values.to_numpy().astype(np.uint8),
+                    "encoding": encoding,
+                    "channels": channels,
+                    "data": arrow_image["data"].values.to_numpy().astype(storage_type),
                 }
 
                 frame = image["data"].reshape(
                     (image["height"], image["width"], image["channels"])
                 )
 
-                frame = frame[:, :, ::-1]  # OpenCV image (BGR to RGB)
+                if encoding == "bgr8":
+                    frame = frame[:, :, ::-1]  # OpenCV image (BGR to RGB)
+
                 results = model(frame, verbose=False)  # includes NMS
 
                 bboxes = np.array(results[0].boxes.xyxy.cpu())