make python example usable without webcam

examples/python-dataflow/no_webcam.py

@@ -0,0 +1,23 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import time
+import urllib.request
+
+import cv2
+import numpy as np
+from dora import Node
+
+req = urllib.request.urlopen(
+    "https://pyimagesearch.com/wp-content/uploads/2015/01/opencv_logo.png"
+)
+
+arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
+node = Node()
+
+start = time.time()
+
+while time.time() - start < 20:
+    # Wait next input
+    node.next()
+    node.send_output("image", arr.tobytes())

examples/python-dataflow/object_detection.py

@@ -1,6 +1,7 @@
 from enum import Enum
 from typing import Callable
 
+import cv2
 import numpy as np
 import torch
 
@@ -35,9 +36,8 @@ class Operator:
         """
 
         frame = np.frombuffer(value, dtype="uint8")
-        frame = np.reshape(frame, (480, 640, 3))[
-            :, :, ::-1
-        ]  # OpenCV image (BGR to RGB)
+        frame = cv2.imdecode(frame, -1)
+        frame = frame[:, :, ::-1]  # OpenCV image (BGR to RGB)
 
         results = self.model(frame)  # includes NMS
         arrays = np.array(results.xyxy[0].cpu()).tobytes()

examples/python-dataflow/plot.py

@@ -35,8 +35,9 @@ class Operator:
         """
         if input_id == "image":
             frame = np.frombuffer(value, dtype="uint8")
-            frame = np.reshape(frame, (480, 640, 3))
+            frame = cv2.imdecode(frame, -1)
             self.image = frame
+
         elif input_id == "bbox" and len(self.image) != 0:
             bboxs = np.frombuffer(value, dtype="float32")
             bboxs = np.reshape(bboxs, (-1, 6))

examples/python-dataflow/webcam.py

@@ -1,50 +1,23 @@
-from enum import Enum
-from typing import Callable
-
-import cv2
-
-
-class DoraStatus(Enum):
-    CONTINUE = 0
-    STOP = 1
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
 
+import time
 
-class Operator:
-    """
-    Example operator incrementing a counter every times its been called.
-
-    The current value of the counter is sent back to dora on `counter`.
-    """
-
-    def __init__(self):
-        self.video_capture = cv2.VideoCapture(0)
-        self.counter = 0
-
-    def on_input(
-        self,
-        input_id: str,
-        value: bytes,
-        send_output: Callable[[str, bytes], None],
-    ) -> DoraStatus:
-        """Handle input by incrementing count by one.
+import cv2
+from dora import Node
 
-        Args:
-            input_id (str): Id of the input declared in the yaml configuration
-            value (bytes): Bytes message of the input
-            send_output (Callable[[str, bytes]]): Function enabling sending output back to dora.
-        """
+node = Node()
 
-        ret, frame = self.video_capture.read()
-        if ret:
-            send_output("image", frame.tobytes())
-        else:
-            print("did not sent video")
+video_capture = cv2.VideoCapture(0)
 
-        self.counter += 1
-        if self.counter > 100:
-            return DoraStatus.STOP
+start = time.time()
 
-        return DoraStatus.CONTINUE
+# Run for 20 seconds
+while time.time() - start < 20:
+    # Wait next input
+    node.next()
+    ret, frame = video_capture.read()
+    if ret:
+        node.send_output("image", cv2.imencode(".jpg", frame)[1].tobytes())
 
-    def drop_operator(self):
-        self.video_capture.release()
+video_capture.release()