Spaces:
Sleeping
Sleeping
File size: 4,645 Bytes
6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 6781c17 7508d11 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
import gradio as gr
import cv2
import torch
import numpy as np
import time
from threading import Thread
import queue
# Load the YOLO model on the CPU
model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
# Global variables for camera control
camera_queue = queue.Queue(maxsize=1)
stop_camera = False
def move_robot(command):
"""
Simulate sending a command to the robot to move.
Replace this with actual communication code to send commands to the robot.
"""
commands = {
"forward": "Robot moving forward",
"backward": "Robot moving backward",
"left": "Robot turning left",
"right": "Robot turning right",
"stop": "Robot stopped"
}
print(commands.get(command, "Invalid command"))
return f"Command sent: {command}"
def camera_loop():
"""Background thread function to continuously capture frames"""
global stop_camera
cap = cv2.VideoCapture(0)
if not cap.isOpened():
print("Error: Could not open camera")
return
while not stop_camera:
ret, frame = cap.read()
if ret:
# Run YOLO detection
results = model(frame)
processed_frame = results.render()[0]
# Convert BGR to RGB for display
processed_frame = cv2.cvtColor(processed_frame, cv2.COLOR_BGR2RGB)
# Update the queue with the latest frame
try:
if camera_queue.full():
camera_queue.get_nowait() # Remove old frame
camera_queue.put_nowait(processed_frame)
except queue.Full:
pass
time.sleep(0.1) # Prevent excessive CPU usage
cap.release()
def start_camera():
"""Start the camera feed"""
global stop_camera
stop_camera = False
Thread(target=camera_loop, daemon=True).start()
return "Camera started"
def stop_camera_feed():
"""Stop the camera feed"""
global stop_camera
stop_camera = True
empty_frame = np.zeros((480, 640, 3), dtype=np.uint8)
return "Camera stopped", empty_frame
def get_current_frame():
"""Get the latest frame from the camera queue"""
try:
frame = camera_queue.get_nowait()
return frame
except queue.Empty:
return np.zeros((480, 640, 3), dtype=np.uint8)
def robot_interface():
with gr.Blocks() as interface:
with gr.Row():
# Left column for controls
with gr.Column(scale=1):
# Control buttons
forward_btn = gr.Button("Forward", variant="primary")
backward_btn = gr.Button("Backward", variant="primary")
left_btn = gr.Button("Left", variant="primary")
right_btn = gr.Button("Right", variant="primary")
stop_btn = gr.Button("Stop", variant="secondary")
status_output = gr.Textbox(label="Robot Status")
# Right column for camera feed
with gr.Column(scale=2):
# Camera feed output
camera_output = gr.Image(
label="Robot Camera Feed with Object Detection",
type="numpy",
height=480,
streaming=True
)
# Start/Stop buttons for camera feed
start_camera_btn = gr.Button("Start Camera", variant="primary")
stop_camera_btn = gr.Button("Stop Camera", variant="secondary")
# Set up button click events for robot movement
forward_btn.click(fn=move_robot, inputs=[gr.Textbox(value="forward", visible=False)], outputs=status_output)
backward_btn.click(fn=move_robot, inputs=[gr.Textbox(value="backward", visible=False)], outputs=status_output)
left_btn.click(fn=move_robot, inputs=[gr.Textbox(value="left", visible=False)], outputs=status_output)
right_btn.click(fn=move_robot, inputs=[gr.Textbox(value="right", visible=False)], outputs=status_output)
stop_btn.click(fn=move_robot, inputs=[gr.Textbox(value="stop", visible=False)], outputs=status_output)
# Set up button click events for camera control
start_camera_btn.click(fn=start_camera, inputs=None, outputs=status_output)
stop_camera_btn.click(fn=stop_camera_feed, inputs=None, outputs=[status_output, camera_output])
# Stream the camera feed
camera_output.stream(fn=get_current_frame)
return interface
# Launch the Gradio interface
if __name__ == "__main__":
robot_interface().launch(share=True, debug=True)
|