def main():
# Capture and
image_capture = ImageCapture(dir_path=IMAGE_DIR_PATH, n_camera=2)
image_capture.capture()
image_path = image_capture.last_captured_path
# Predict
model_path = MODEL_PATH
client = LocalPredictApiClient(model_path)
pred_result = client.predict(image_path)
# Save
prediction_data = PredictionData(
image_path=image_path,
prediction=pred_result['prediction'],
json_result=str(pred_result),
capture_datetime_local=image_capture.capture_datetime_local,
capture_datetime_utc=image_capture.capture_datetime_utc)
prediction_ds = PredictionDataStore(DB_DIR_PATH)
prediction_ds.save(prediction_data)
if not os.path.exists(newpath):
os.makedirs(newpath)
imagefile = datafolder + filename + '.png'
textfile = open(datafolder + filename + '.txt', 'a')
file_operations.save_to_folder(textfile, imagefile, bounding_box, final)
# todo get classes through GUI
classes = []
#interface = CLI()
file_operations = FileOperations()
motor = MotorControl()
camera = ImageCapture(RPI_CAMERA)
image_processor = ImageProcessing(camera.capture())
delay = 1 / 1000.0
#images = input("How many images do you want per category (5 categories)?")
images = 10000
STEPS_FOR_FULL_CIRCLE = 12360
steps = int(STEPS_FOR_FULL_CIRCLE / images)
classes = ["Banana"] #, "Rolle"]
only_snippets = False
only_train_images = True
## Section for the configuration
# Make images for every class
for label in classes:
if only_train_images:
from image_capture import ImageCapture
from image_processing import ImageProcessing
import cv2
import numpy as np
camera = ImageCapture()
#camera = cv2.VideoCapture(0)
processor = ImageProcessing()
while True:
img_raw = camera.capture()
img_cut = img_raw[:,
int(np.shape(img_raw)[1] * 1 /
5):int(np.shape(img_raw)[1] * 4 / 5), :]
img_gray = processor.gray(img_cut)
edge = processor.canny(img_gray)
contour = processor.max_contour(edge)
cv2.drawContours(img_cut, contour, -1, (0, 255, 0), 3)
bounding_box = processor.bounding_box(contour)
print(bounding_box)
#if bounding_box != -1:
# print("success!")
#else:
# print("failure!")
cv2.imshow('raw_image', img_raw)
cv2.imshow('cut_image', img_cut)
cv2.imshow('gray_image', img_gray)
cv2.imshow('canny_image', edge)
cv2.waitKey(20)