def face_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QVGA)
faces = sensor.snapshot().gamma_corr(contrast=1.5).find_features(image.HaarCascade("frontalface"))
if not faces: return bytes() # No detections.
for f in faces: sensor.get_fb().draw_rectangle(f, color = (255, 255, 255))
out_face = max(faces, key = lambda f: f[2] * f[3])
return struct.pack("<HHHH", out_face[0], out_face[1], out_face[2], out_face[3])
def color_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QVGA)
thresholds = struct.unpack("<bbbbbb", data)
blobs = sensor.snapshot().find_blobs([thresholds],
pixels_threshold=500,
area_threshold=500,
merge=True,
margin=20)
if not blobs: return bytes() # No detections.
for b in blobs:
sensor.get_fb().draw_rectangle(b.rect(), color = (255, 0, 0))
sensor.get_fb().draw_cross(b.cx(), b.cy(), color = (0, 255, 0))
out_blob = max(blobs, key = lambda b: b.density())
return struct.pack("<HH", out_blob.cx(), out_blob.cy())
def raw_image_read(data):
if not len(data):
interface.schedule_callback(raw_image_read_cb)
return bytes()
else:
offset, size = struct.unpack("<II", data)
return memoryview(sensor.get_fb().bytearray())[offset:offset+size]
def all_apriltag_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
tags = sensor.snapshot().find_apriltags()
if not tags: return bytes() # No detections.
draw_detections(sensor.get_fb(), tags)
return str(tags).encode()
def all_datamatrix_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((320, 240))
codes = sensor.snapshot().find_datamatrices()
if not codes: return bytes() # No detections.
draw_detections(sensor.get_fb(), codes)
return str(codes).encode()
def datamatrix_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((320, 240))
codes = sensor.snapshot().find_datamatrices()
if not codes: return bytes() # No detections.
draw_detections(sensor.get_fb(), codes)
return max(codes, key = lambda c: c.w() * c.h()).payload().encode()
def apriltag_detection(data):
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
tags = sensor.snapshot().find_apriltags()
if not tags: return bytes() # No detections.
draw_detections(sensor.get_fb(), tags)
output_tag = max(tags, key = lambda t: t.w() * t.h())
return struct.pack("<HHHH", output_tag.cx(), output_tag.cy(), output_tag.id(),
int(math.degrees(output_tag.rotation())))
def raw_image_read_cb():
global processing
interface.put_bytes(sensor.get_fb().bytearray(), 5000) # timeout
processing = False
def raw_image_read_cb():
interface.put_bytes(sensor.get_fb().bytearray(), 5000) # timeout
def loop(control, thermal, screen, menu, input_handler, camera_slave, **kwargs):
led_green = LED(2) # red led
led_green.off()
usb = pyb.USB_VCP()
running_from_ide = usb.isconnected()
def camera_slave_sync_cancel_condition():
if control.preview is not CameraPreview.VISIBLE or menu.state is not CameraState.PREVIEW:
logger.info("Cancel camera slave sync")
return True
return False
camera_slave.sync_cancel_condition = camera_slave_sync_cancel_condition
state = None
camera_preview = None
camera_playback_img_name = ""
previous_text = ""
screen_refresh_needed = True
state_ticks_ms = utime.ticks_ms()
menu.process_action("middle")
while True:
changed_state = state is not menu.state
state = menu.state
changed_preview = camera_preview is not control.preview
camera_preview = control.preview
# -----------------------------------------------------------------------------------------
# INITIALIZATIONS
if changed_state:
state_ticks_ms = utime.ticks_ms()
logger.info("Processing state change to ", menu.state)
if menu.state is CameraState.PREVIEW:
control.fps_reset()
if menu.state is CameraState.PLAYBACK or menu.state is CameraState.POSTVIEW:
#control.set_normal_resolution()
control.update_playback_img_name(go_to_last=True)
camera_playback_img_name = ""
if changed_preview:
control.fps_reset()
logger.info("Processing preview change to ", control.preview)
# -----------------------------------------------------------------------------------------
# RUN TIME
if state is CameraState.PREVIEW:
control.fps_tick()
screen_refresh_needed = True
text = "\n" + menu.generate_text()
if camera_preview is CameraPreview.THERMAL or camera_preview is CameraPreview.THERMAL_ANALYSIS or camera_preview is CameraPreview.THERMAL_GREY or camera_preview is CameraPreview.MIX:
thermal.get_spotmeter_values()
def map_g_to_temp(g):
return ((g * (thermal.temperature_max - thermal.temperature_min)) / 255.0) + thermal.temperature_min
img = sensor.snapshot()
img_touch_x = max(0,min(sensor.width() - 1, round(control.x * sensor.width()/screen.width) ))
img_touch_y = max(0,min(sensor.height() - 1, round(control.y * sensor.height()/screen.height) ))
pixel = "{:.2f}".format(map_g_to_temp(img.get_pixel(img_touch_x, img_touch_y)))
if camera_preview is CameraPreview.THERMAL_GREY:
img.to_rgb565()
elif camera_preview is CameraPreview.THERMAL or camera_preview is CameraPreview.MIX:
img.to_rainbow(color_palette=sensor.PALETTE_IRONBOW) # color it
elif camera_preview is CameraPreview.THERMAL_ANALYSIS:
# Color tracking concept from lepton_object_temp_color_1.py in the OpenMV examples
# Color Tracking Thresholds (Grayscale Min, Grayscale Max)
threshold_list = [(200, 255)]
blob_stats = []
blobs = img.find_blobs(threshold_list, pixels_threshold=200, area_threshold=200, merge=True)
# Collect stats into a list of tuples
for blob in blobs:
blob_stats.append((blob.x(), blob.y(), map_g_to_temp(img.get_statistics(thresholds=threshold_list,
roi=blob.rect()).mean())))
img.to_rainbow(color_palette=sensor.PALETTE_IRONBOW) # color it
# Draw stuff on the colored image
for blob in blobs:
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
for blob_stat in blob_stats:
img.draw_string(blob_stat[0], blob_stat[1] - 10, "%.2f C" % blob_stat[2], mono_space=False)
qqvga2qvga(sensor.get_fb(), screen.screen_buff)
if camera_preview is CameraPreview.VISIBLE or camera_preview is CameraPreview.MIX:
input_handler.disable()
sync_success = camera_slave.sync()
input_handler.enable()
if not sync_success:
logger.info("Failed sync")
screen.screen_buff.fill(c=(10,10,10))
screen.screen_buff.draw_string(screen.width//2, screen.height//2, "ERROR", c=(255,0,0))
if camera_preview is CameraPreview.VISIBLE:
qvga2qvga(camera_slave.rx_buff, screen.screen_buff, 0, 1)
pixel = screen.screen_buff.get_pixel(control.x, control.y)
elif camera_preview is CameraPreview.MIX:
qvga2qvga(camera_slave.rx_buff, screen.screen_buff, 0, 2)
if menu.page != "ROOT" or control.always_pixel_pointer:
screen.screen_buff.draw_rectangle(control.x-5, control.y-5, 10, 10, color=(255,0,255), thickness=1, fill=True)
if menu.state is CameraState.PREVIEW:
text_y_offset = 50 if control.y < screen.height//2 else -50
screen.screen_buff.draw_string(control.x - 20, control.y + text_y_offset, "{}".format(pixel))
if state is CameraState.PLAYBACK or state is CameraState.POSTVIEW:
screen_refresh_needed = False
if menu.page == "ANALYSIS":
screen_refresh_needed = True
text = menu.generate_text()
if previous_text != text:
screen_refresh_needed = True
if not control.playback_img_name:
logger.info("No image to be loaded")
menu.back()
continue
elif control.playback_img_name != camera_playback_img_name or screen_refresh_needed:
camera_playback_img_name = control.playback_img_name
logger.info("Displaying image...", control.playback_img_name, " and text ", text)
try:
img = image.Image(control.playback_img_name, copy_to_fb=True)
qvga2qvga(sensor.get_fb(), screen.screen_buff, 0, 1)
if control.to_save_fb_as_startup:
control.save_fb_as_startup(screen.screen_buff)
img.to_grayscale()
try:
file_name = control.playback_img_name.split("/")[-1].split(".")[0]
file_name = file_name.split("_")
thermal.temperature_min = float(file_name[1]) / 100
thermal.temperature_max = float(file_name[2]) / 100
except Exception as e:
print("Could not get min and max from name", e)
print("file_name", file_name, thermal.temperature_min, thermal.temperature_max)
except OSError as e:
screen.screen_buff.draw_rectangle(0, 0, screen.width, screen.height, color=(30,30,30), fill=True)
screen.screen_buff.draw_string(round(screen.width/6), round(screen.height/2.3), "ERROR LOADING...", color=(255,0,0), scale=2.0)
logger.info("Error while loading ", control.playback_img_name, ". Try Again. Error", e)
if menu.page == "ANALYSIS":
def map_g_to_temp(g):
return ((g * (thermal.temperature_max - thermal.temperature_min)) / 255.0) + thermal.temperature_min
img_touch_x = max(0,min(sensor.width() - 1, round(control.x * sensor.width()/screen.width) ))
img_touch_y = max(0,min(sensor.height() - 1, round(control.y * sensor.height()/screen.height) ))
pixel = "{:.2f}".format(map_g_to_temp(img.get_pixel(img_touch_x, img_touch_y)))
screen.screen_buff.draw_rectangle(control.x-5, control.y-5, 10, 10, color=(255,0,255), thickness=1, fill=True)
text_y_offset = 50 if control.y < screen.height//2 else -50
screen.screen_buff.draw_string(control.x - 20, control.y + text_y_offset, "{}".format(pixel))
screen_refresh_needed = True
if state is CameraState.POSTVIEW and utime.ticks_diff(utime.ticks_ms(), state_ticks_ms) > 2000:
menu.back()
########################################################################
# INPUT TASKS which are BIG
if control.to_save_img:
control.save_img(screen.screen_buff, thermal.temperature_min, thermal.temperature_max)
menu.process_action("postview")
led_green.on()
utime.sleep_ms(100)
led_green.off()
########################################################################
# DISPLAY IN SCREEN
if menu.state is CameraState.PLAYBACK and menu.page == "MENU":
screen.screen_buff.draw_rectangle(0,0,screen.width//2,screen.height,color=(0,0,0), fill=True)
if screen_refresh_needed:
previous_text = text
screen.screen_buff.draw_string(10, 10, text, color=(57, 255, 20), scale=2.1, mono_space=False)
if state is CameraState.PLAYBACK:
logger.info("Refresh needed")
screen.write_to_screen(screen.screen_buff)
screen_refresh_needed = False
########################################################################
# OTHER FUNCTIONALITY
if not running_from_ide and usb.isconnected():
screen.screen_buff.draw_rectangle(0, screen.height//3, screen.width, screen.height//3, color=(10,10,10), fill=True)
screen.screen_buff.draw_string(round(screen.width/5), round(screen.height/2.3), "USB DEBUGGING", color=(255,0,0), scale=2.0)
screen.write_to_screen(screen.screen_buff)
utime.sleep_ms(500)
input_handler.disable()
exit(0)
if input_handler.pin.value() == 0 and input_handler.time_since_interrupt() > 100:
input_handler.interrupt_callback(line="LOOP")
gc.collect()
sensor.set_contrast(+2)
sensor.set_brightness(+3)
sensor.set_auto_gain(True)
sensor.skip_frames(time=2000)
clock = time.clock()
min_degree = 0
max_degree = 179
while (True):
clock.tick()
img = sensor.snapshot()
line_img = sensor.get_fb()
cir_img = sensor.get_fb()
cir_img.gaussian(2)
cir_img.binary([(40, 100)])
if enable_lens_corr: img.lens_corr(1.8) # for 2.8mm lens...
for c in cir_img.find_circles(threshold=4000,
x_margin=10,
y_margin=10,
r_margin=60,
r_min=2,
r_max=20,
r_step=4):
img.draw_circle(c.x(), c.y(), c.r(), color=(255, 0, 0))
# Use this script to gather face images for building a TensorFlow dataset. This script automatically
# zooms in the largest face in the field of view which you can then save using the data set editor.
import sensor, image, time
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time=2000)
clock = time.clock()
largest_face = None
largest_face_timeout = 0
while (True):
clock.tick()
faces = sensor.snapshot().gamma_corr(contrast=1.5).find_features(
image.HaarCascade("frontalface"))
if faces:
largest_face = max(faces, key=lambda f: f[2] * f[3])
largest_face_timeout = 20
if largest_face_timeout > 0:
sensor.get_fb().crop(roi=largest_face)
largest_face_timeout -= 1
print(clock.fps())
import VPOST as VP
import sensor
#Enable frame layer
disp = VP.display(ColorFormat=VP.YCBYCR)
disp.init()
sensor.reset()
sensor.set_pixformat(sensor.YUV422P, sensor.YUV422)
sensor.set_framesize(sensor.VGA, sensor.QVGA)
planar_img = sensor.get_fb(sensor.PIPE_PLANAR)
packet_img = sensor.get_fb(sensor.PIPE_PACKET)
sensor.skip_frames()
while True:
sensor.snapshot(planar_image=planar_img, packet_image=packet_img)
disp.render_image(packet_img)
sensor.skip_frames(100)
sensor.run(1)
# Find /SD
if uos.getcwd() != "/sd":
sd_flag = False
else:
sd_flag = True
clock = utime.clock()
img_cnt = 0
while True:
# Transfer a frame to PC
led_r.value(0)
fbuffer = sensor.get_fb()
img = sensor.snapshot()
fbuffer = img
led_r.value(1)
# Display img to LCD
led_g.value(0)
lcd.display(img)
led_g.value(1)
# Write img to SD
led_b.value(0)
if button_a.value() == 0:
if sd_flag is True:
file_name = "img_" + str(img_cnt) + ".jpg"
lcd.draw_string(10, 10, file_name + " is taken!")
blank = array.array('d', [0, 0, 0, 0, 0, 0])
print(blank)
usb.send(array.array('d', [0, 0, 0, 0, 0, 0]),
timeout=round(1000 / fps))
clock.tick()
while (usb.isconnected()):
#img.draw_circle(ring.x(), ring.y(), ring.r(), color = (255, 0, 0))
# img.draw_cross(ring.x(), ring.y(), color = (255, 0, 0))
gc.collect()
sensor.snapshot().histeq(adaptive=True, clip_limit=2.5)
#img.morph(kernel_size, kernel) # Run the kernel on every pixel of the image.
maxButt = 0
maxHead = 0
for blob in sensor.get_fb().find_blobs(thresholds,
pixels_threshold=6,
area_threshold=10):
if blob.code() == buttColor and (blob.area()) > maxButt: #butt
maxButt = blob.area()
butt = blob
#img.draw_keypoints([(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=20)
if blob.code() == headColor and (blob.area()) > maxHead: #head
maxHead = blob.area()
head = blob
#img.draw_keypoints([(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=20)
if maxButt * maxHead > 0:
img.draw_string(butt.x() + 2, butt.y() + 2, "butt")
img.draw_string(head.x() + 2, head.y() + 2, "head")
headV = [head.cxf() - ring.x(), head.cyf() - ring.y()]