Update cmd.py to new VisionClient

python/cmd.py

@@ -1,49 +1,58 @@
-import asyncio
+import asyncio,os
 
 from viam.robot.client import RobotClient
 from viam.rpc.dial import Credentials, DialOptions
-from viam.services.vision import VisionServiceClient
+from viam.services.vision import VisionClient
 from viam.components.camera import Camera
-import numpy as np
 import cv2
+import numpy as np
 
+##on command line run:
+##export ROBOT_SECRET=your_robot_secret from app.viam.com
+##export ROBOT_ADDRESS=your_robot_address from app.viam.com
 
 async def connect():
     creds = Credentials(
         type='robot-location-secret',
-        payload='[PUT  IN INFO FROM ROBOT CONNECT TAB ON APP]')
+        payload=os.getenv('ROBOT_SECRET'))
     opts = RobotClient.Options(
         refresh_interval=0,
         dial_options=DialOptions(credentials=creds)
     )
-    return await RobotClient.at_address('[INFO FROM ROBOT CONNECT TAB ON APP]', opts)
-
+    return await RobotClient.at_address(os.getenv('ROBOT_ADDRESS'), opts)
 
 async def main():
-    # establish a connection to the robot client
+
     robot = await connect()
     # grab camera from the robot
-    cam1 = Camera.from_robot(robot, "cam1")
-    # grab your vision service, here named "myDetector", which has the TFLite detector already registered
-    myDetector = VisionServiceClient.from_robot(robot, "myDetector")
-    # make a display window
+    cam1 = Camera.from_robot(robot, "web_cam")
+    # grab Viam's vision service for the detector
+    my_detector = VisionClient.from_robot(robot, "vision_svc")
+
     cv2.namedWindow('object_detect', cv2.WINDOW_NORMAL)
     # loop forever:  find objects using Viam Vision, and draw boxes aroung them using openCV
-    while(True):
-        img = await cam1.get_image() # default is JPEG
-        detections = await myDetector.get_detections(img)
-        # turn image into numpy array
-        pix = np.array(img, dtype=np.uint8)
-        pix = cv2.cvtColor(pix, cv2.COLOR_RGB2BGR)
-        # put boxes around objects with enough confidence (> 0.6)
-        conf = 0.6
-        for d in detections:
-            if d.confidence > conf:
-                cv2.rectangle(pix, (d.x_min, d.y_min), (d.x_max, d.y_max), (0, 0, 255), 3)
-        cv2.imshow('object_detect',pix)
-        cv2.waitKey(1)
-
-    await robot.close()
+    try:
+        while(True):
+            print("hi")
+            img = await cam1.get_image()
+            detections = await my_detector.get_detections(img)
+            print(detections)
+            # turn image into numpy array
+            pix = np.array(img, dtype=np.uint8)
+            pix = cv2.cvtColor(pix, cv2.COLOR_RGB2BGR)
+            # put boxes around objects with enough confidence (> 0.6)
+            conf = 0.6
+            for d in detections:
+                if d.confidence > conf:
+                    cv2.rectangle(pix, (d.x_min, d.y_min), (d.x_max, d.y_max), (0, 0, 255), 3)
+            cv2.imshow('object_detect',pix)
+            cv2.waitKey(1)
+    finally:
+        print("closing robot")
+        await robot.close()
+        print("robot closed")
+
 
 if __name__ == '__main__':
     asyncio.run(main())
+