def hanlde_endpoint_scan(self, image, json) -> int:
filename, full_path = compute_file_name()
# Save the image using the flask file
image.save(full_path)
scan_request = ScanRequest.from_request(json, filename)
return self.handle_scan(scan_request, filename)
def create_scan():
img: np.ndarray = cv.imread("raw.jpg")
depth_map = np.random.rand(img.shape[0], img.shape[1])
scan_req = ScanRequest(img, depth_map, 2, 1)
from tray_system.data_pusher import DataPusher
dp = DataPusher()
dp.push_scan(scan_req)
def hanlde_endpoint_scan(self, image, json) -> int:
filename, full_path = compute_file_name()
# Save the image using the flask file
image.save(full_path)
scan_request = ScanRequest.from_request(json, filename)
return self.handle_scan(scan_request, filename)
def scan(self):
if self.last_rfid is None:
print("Tried to scan without RFID")
return
colour_img, depth_img = self.realsense_capturer.capture()
print(colour_img.shape)
print(depth_img.shape)
menu_item_id = 1 # Get this from RFID
user_id = 1
scan_request = ScanRequest(colour_img, depth_img, menu_item_id, user_id)
if COMPUTE_LOCAL:
return self.scan_handler.handle_local_scan(scan_request)
return self.data_pusher.push_scan(scan_request)
def push_scan(self, scan_request: ScanRequest):
_, img_encoded = cv.imencode('.jpg', scan_request.image)
payload = {
'json': (None, scan_request.get_json(), 'application/json'),
'image': ("ignored.jpg", img_encoded),
}
resp = requests.post(Endpoint.SCAN.get(), files=payload)
if resp.status_code == requests.codes.ok:
print("Successfully pushed scan to server")
else:
print("Unable to push scan to server")
# TODO: Return scan id
return resp.data
# max_depth_in_circle = segmented_circle.get_max_value_in_circle(depth_map)
# print("Max depth in circle was %d" % max_depth_in_circle)
# depth_map = max_depth_in_circle - depth_map
for segment in segmented_circle.segments:
ingredient = self.ingredient_detector.label(
segment.get_segment_of(image))
if ingredient is None:
continue
mass = calculate_mass(depth_map, segment, mm_per_pixel)
print(mass)
detection: Detection = Detection(segment.x1, segment.y1, mass)
detected_ingredients[ingredient].append(detection)
results = [
DetectedIngredient(scan_id, k.id, v)
for (k, v) in detected_ingredients.items()
]
print("Found {} detected ingredients: {}".format(
len(results), [r.ingredient_id for r in results]))
return results
if __name__ == "__main__":
img: np.ndarray = cv.imread("../../test.jpg")
depth_map = 500 * np.random.rand(img.shape[0], img.shape[1])
scan_req = ScanRequest(img, depth_map, 1, 1)
from tray_system.data_pusher import DataPusher
dp = DataPusher()
dp.push_scan(scan_req)
# detector.run_detection(scan_req)
def run_live(ingredient_detector):
data_pusher = DataPusher()
pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.depth, REALSENSE_WIDTH, REALSENSE_HEIGHT, rs.format.z16, 30)
config.enable_stream(rs.stream.color, REALSENSE_WIDTH, REALSENSE_HEIGHT, rs.format.bgr8, 30)
align_to = rs.stream.color
align = rs.align(align_to)
# Start streaming
pipeline.start(config)
colorizer = rs.colorizer()
hole_filler = rs.hole_filling_filter()
# Skip 5 first frames to give the Auto-Exposure time to adjust
for x in range(5):
pipeline.wait_for_frames()
while True:
frames = pipeline.wait_for_frames(timeout_ms=5000)
aligned_frames = align.process(frames)
color = aligned_frames.get_color_frame()
depth = aligned_frames.get_depth_frame()
# depth = hole_filler.process(depth)
# depth2 = depth.get_distance(100, 100)
# print(depth2)
if not depth or not color:
continue
depth_frame_data = np.asanyarray(depth.get_data())
color_frame_data = np.asanyarray(color.get_data())
depth_image = np.asanyarray(colorizer.colorize(depth).get_data(), dtype=np.uint8)
# depth_image = np.asanyarray(depth.get_data(), dtype=np.uint8)
color_image = np.asanyarray(color.get_data(), dtype=np.uint8)
color_image_with_overlay = np.copy(color_image)
# cv.imwrite("rgb.jpg", color_image)
# cv.imwrite("depth.jpg", depth_image)
process_colour_image(color_image_with_overlay, ingredient_detector)
circle_detector.draw_segmented_circle(color_image_with_overlay)
if cv.waitKey(1) & 0xFF == ord(' '):
# np.save("colour.txt", color_image)
# np.save("depth.txt", np.asanyarray(depth.get_data(), dtype=np.uint8))
# r = color_image[:, :, 0]
# g = color_image[:, :, 1]
# b = color_image[:, :, 2]
# np.savetxt("colour-r.txt", r)
# np.savetxt("colour-g.txt", g)
# np.savetxt("colour-b.txt", b)
# np.savetxt("depth.txt", np.asanyarray(depth.get_data(), dtype=np.uint8))
scan_request = ScanRequest(color_frame_data, depth_frame_data, 1, 1)
data_pusher.push_scan(scan_request)
check_for_key()
cv.imshow("Depth", depth_image)
cv.imshow("RGB", color_image_with_overlay)
sleep(0.2)