Can not run app in device

[ducnmisbk]

Hi @twelve17 ,

Would you please give me some help? I'm getting errors when trying to run app in device. (Run app in simulator is ok)

Output log:

Missing config value for runtime_dir
Missing config value for detector
Missing config value for detection_iteration_increase
Missing config value for detection_strictness
Missing config value for max_plate_width_percent
Missing config value for max_plate_height_percent
Missing config value for max_detection_input_width
Missing config value for max_detection_input_height
Missing config value for contrast_detection_threshold
Missing config value for must_match_pattern
Missing config value for skip_detection
Missing config value for detection_mask_image
Missing config value for analysis_count
Missing config value for prewarp
Missing config value for max_plate_angle_degrees
Missing config value for ocr_img_size_percent
Missing config value for state_id_img_size_percent
Missing config value for ocr_min_font_point
Missing config value for postprocess_min_confidence
Missing config value for postprocess_confidence_skip_level
Missing config value for debug_general
Missing config value for debug_timing
Missing config value for debug_prewarp
Missing config value for debug_detector
Missing config value for debug_state_id
Missing config value for debug_plate_lines
Missing config value for debug_plate_corners
Missing config value for debug_char_segment
Missing config value for debug_char_analysis
Missing config value for debug_color_filter
Missing config value for debug_ocr
Missing config value for debug_postprocess
Missing config value for debug_show_images
Missing config value for debug_pause_on_frame

[agoodmiller]

Did you ever get this solved? I am having the same issue

[ducnmisbk]

@agoodmiller : I resolved with below configs.

; Specify the path to the runtime data directory
runtime_dir = ${CMAKE_INSTALL_PREFIX}/share/openalpr/runtime_data

ocr_img_size_percent = 1.33333333
state_id_img_size_percent = 2.0

; Calibrating your camera improves detection accuracy in cases where vehicle plates are captured at a steep angle
; Use the openalpr-utils-calibrate utility to calibrate your fixed camera to adjust for an angle
; Once done, update the prewarp config with the values obtained from the tool
prewarp =

; detection will ignore plates that are too large.  This is a good efficiency technique to use if the
; plates are going to be a fixed distance away from the camera (e.g., you will never see plates that fill
; up the entire image
max_plate_width_percent = 100
max_plate_height_percent = 100

; detection_iteration_increase is the percentage that the LBP frame increases each iteration.
; It must be greater than 1.0.  A value of 1.01 means increase by 1%, 1.10 increases it by 10% each time.
; So a 1% increase would be ~10x slower than 10% to process, but it has a higher chance of landing
; directly on the plate and getting a strong detection
detection_iteration_increase = 1.1

; The minimum detection strength determines how sure the detection algorithm must be before signaling that
; a plate region exists.  Technically this corresponds to LBP nearest neighbors (e.g., how many detections
; are clustered around the same area).  For example, 2 = very lenient, 9 = very strict.
detection_strictness = 3

; The detection doesn't necessarily need an extremely high resolution image in order to detect plates
; Using a smaller input image should still find the plates and will do it faster
; Tweaking the max_detection_input values will resize the input image if it is larger than these sizes
; max_detection_input_width/height are specified in pixels
max_detection_input_width = 4000
max_detection_input_height = 4000

; detector is the technique used to find license plate regions in an image.  Value can be set to
; lbpcpu    - default LBP-based detector uses the system CPU
; lbpgpu    - LBP-based detector that uses Nvidia GPU to increase recognition speed.
; lbpopencl - LBP-based detector that uses OpenCL GPU to increase recognition speed.  Requires OpenCV 3.0
; morphcpu  - Experimental detector that detects white rectangles in an image.  Does not require training.
detector = lbpcpu

; If set to true, all results must match a postprocess text pattern if a pattern is available.
; If not, the result is disqualified.
must_match_pattern = 0

; Bypasses plate detection.  If this is set to 1, the library assumes that each region provided is a likely plate area.
skip_detection = 0

; 35-50; 45-60, 55-70, 65-80, 75-90
char_analysis_min_pct = 0.35
char_analysis_height_range = 0.15
char_analysis_height_step_size = 0.10
char_analysis_height_num_steps = 5

segmentation_min_speckle_height_percent = 0.2
segmentation_min_box_width_px = 5
segmentation_min_charheight_percent = 0.4;
segmentation_max_segment_width_percent_vs_average = 2.0;

plate_width_mm = 520
plate_height_mm = 110

multiline = 0

char_height_mm = 80
char_width_mm = 53
char_whitespace_top_mm = 10
char_whitespace_bot_mm = 10

template_max_width_px = 184
template_max_height_px = 46

; Higher sensitivity means less lines
plateline_sensitivity_vertical = 18
plateline_sensitivity_horizontal = 55

; Regions smaller than this will be disqualified
min_plate_size_width_px = 65
min_plate_size_height_px = 18

; Results with fewer or more characters will be discarded
postprocess_min_characters = 5
postprocess_max_characters = 8

ocr_language = leu

; Override for postprocess letters/numbers regex.
postprocess_regex_letters = [A-Z]
postprocess_regex_numbers = [0-9]

; Whether the plate is always dark letters on light background, light letters on dark background, or both
; value can be either always, never, or auto
invert = auto

; OpenALPR detects high-contrast plate crops and uses an alternative edge detection technique.  Setting this to 0.0
; would classify  ALL images as high-contrast, setting it to 1.0 would classify no images as high-contrast.
contrast_detection_threshold = 0.3

; Specifies the full path to an image file that constrains the detection area.  Only the plate regions allowed through the mask
; will be analyzed.  The mask image must match the resolution of your image to be analyzed.  The mask is black and white.
; Black areas will be ignored, white areas will be searched.  An empty value means no mask (scan the entire image)
detection_mask_image =

; OpenALPR can scan the same image multiple times with different randomization.  Setting this to a value larger than
; 1 may increase accuracy, but will increase processing time linearly (e.g., analysis_count = 3 is 3x slower)
analysis_count = 1

; OpenALPR detects high-contrast plate crops and uses an alternative edge detection technique.  Setting this to 0.0
; would classify  ALL images as high-contrast, setting it to 1.0 would classify no images as high-contrast.
contrast_detection_threshold = 0.3

max_plate_angle_degrees = 15

ocr_min_font_point = 6

; Minimum OCR confidence percent to consider.
postprocess_min_confidence = 65

; Any OCR character lower than this will also add an equally likely
; chance that the character is incorrect and will be skipped.  Value is a confidence percent
postprocess_confidence_skip_level = 80

debug_general         = 0
debug_timing          = 0
debug_detector        = 0
debug_prewarp         = 0
debug_state_id        = 0
debug_plate_lines     = 0
debug_plate_corners   = 0
debug_char_segment    = 0
debug_char_analysis   = 0
debug_color_filter    = 0
debug_ocr             = 0
debug_postprocess     = 0
debug_show_images     = 0
debug_pause_on_frame  = 0

[snamrata007]

Where does it need to replace configs?

[robertmzm]

Where does it need to replace configs?

/usr/local/share/openalpr/config