def read_camera(path, camera, cnt):
#print("Tryna Read")
img = camera.read()
jpg = bgr8_to_jpeg(img)
f = open(path.replace("*", str(cnt)), "wb")
f.write(jpg)
f.close()
def execute(change):
image = change['new']
data = preprocess(image)
cmap, paf = model_trt(data)
cmap, paf = cmap.detach().cpu(), paf.detach().cpu()
counts, objects, peaks = parse_objects(
cmap, paf) #, cmap_threshold=0.15, link_threshold=0.15)
draw_objects(image, counts, objects, peaks)
image_w.value = bgr8_to_jpeg(image[:, ::-1, :])
def __execute(self, change):
image = change['new']
data = self.__preprocess(image)
cmap, paf = self.model_trt(data)
cmap, paf = cmap.detach().cpu(), paf.detach().cpu()
counts, objects, peaks = self.parse_objects(cmap, paf)
keypoints = self.keypoint_coordinates(image, counts, objects, peaks)
self.image_pub.publish(self.bridge.cv2_to_imgmsg(image, "bgr8"))
if self.display_widget:
self.display_widget.value = bgr8_to_jpeg(image[:, ::-1, :])
else:
self.display.set_data(image[:, :, ::-1])
plt.pause(0.000001)
return keypoints
def save_snapshot(_, content, msg):
if content['event'] == 'click':
data = content['eventData']
x = data['offsetX']
y = data['offsetY']
# save to disk
dataset.save_entry(category_widget.value, camera.value, x, y)
# display saved snapshot
snapshot = camera.value.copy()
snapshot = cv2.circle(snapshot, (x, y), 8, (0, 255, 0), 3)
snapshot_widget.value = bgr8_to_jpeg(snapshot)
count_widget.value = dataset.get_count(category_widget.value)
def live(state_widget, model, camera, prediction_widget):
global dataset
while state_widget.value == 'live':
image = camera.value
preprocessed = preprocess(image)
output = model(preprocessed).detach().cpu().numpy().flatten()
category_index = dataset.categories.index(category_widget.value)
x = output[2 * category_index]
y = output[2 * category_index + 1]
x = int(camera.width * (x / 2.0 + 0.5))
y = int(camera.height * (y / 2.0 + 0.5))
prediction = image.copy()
prediction = cv2.circle(prediction, (x, y), 8, (255, 0, 0), 3)
prediction_widget.value = bgr8_to_jpeg(prediction)
def execute(change):
global frame_num
frame_num = frame_num + 1
image = change['new']
data = preprocess(image)
cmap, paf = model_trt(data)
cmap, paf = cmap.detach().cpu(), paf.detach().cpu()
counts, objects, peaks = parse_objects(cmap, paf)#, cmap_threshold=0.15, link_threshold=0.15)
draw_objects(image, counts, objects, peaks)
# image = cv2.rotate(image, cv2.cv2.ROTATE_90_COUNTERCLOCKWISE)
image_w.value = bgr8_to_jpeg(image[:, ::-1, :])
clear_output(wait=True)
keypoints = []
for keypoint in peaks[0]:
keypoints.append(keypoint[0])
print_to_file(keypoints)
print(f"{keypoints}", end='\r')
"""
Simple test script to validate the motor controls and the steering and the camera and the ultrasonic sensors
"""
from jetcam.csi_camera import CSICamera
import ipywidgets
from IPython.display import display
from jetcam.utils import bgr8_to_jpeg
camera_in = CSICamera(width=224,
height=224,
capture_width=1080,
capture_height=720,
capture_fps=30) # Default Nvidia Camera Setup
image_widget = ipywidgets.Image(format='jpeg')
while True:
image_widget.value = bgr8_to_jpeg(camera_in.read())
display(image_widget)
# Test motors
import actuators
drive_train = actuators.ServoMotor()
def read_camera(path, camera, cnt):
img = camera.read()
jpg = bgr8_to_jpeg(img)
f = open(path + "car_frame_" + str(cnt) + ".jpg", "wb")
f.write(jpg)
f.close()
from jetcam.csi_camera import CSICamera camera = CSICamera(width=224, height=224) image = camera.read() print(image.shape) print(camera.value.shape) import ipywidgets from IPython.display import display from jetcam.utils import bgr8_to_jpeg image_widget = ipywidgets.Image(format='jpeg') image_widget.value = bgr8_to_jpeg(image) display(image_widget)
def read_camera(camera, cnt):
img = camera.read()
jpg = bgr8_to_jpeg(img)
f = open("images/cap" + str(cnt) + ".jpg", "wb")
f.write(jpg)
f.close()
import os
import traitlets
#import ipywidgets.widgets as widgets
#from IPython.display import display
#from jetbot import Camera, bgr8_to_jpeg
from uuid import uuid1
from jetcam.usb_camera import USBCamera
from jetcam.utils import bgr8_to_jpeg
directory = '.'
# Start the camera and create a video stream
#camera = USBCamera(capture_device=1)
camera = USBCamera(width=224,
height=224,
capture_width=640,
capture_height=480,
capture_device=0)
print(camera.value.shape)
# Get an bgr8 image from the camera
image = camera.read()
print(camera.value.shape)
toJpeg = bgr8_to_jpeg(image)
image_path = os.path.join(directory, str(uuid1()) + '.jpg')
with open(image_path, 'wb') as f:
f.write(image.value)
def update_image(change):
image = change['new']
image_widget.value = bgr8_to_jpeg(image)
