How to use test_sample_collection method in molecule

Best Python code snippet using molecule_python

test_lab_test.py

Source:test_lab_test.py Github

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...32 lab_test.descriptive_test_items[0].result_value = 1233 lab_test.descriptive_test_items[2].result_value = 134 lab_test.save()35 self.assertRaises(frappe.ValidationError, lab_test.submit)36 def test_sample_collection(self):37 frappe.db.set_value('Healthcare Settings', 'Healthcare Settings', 'create_sample_collection_for_lab_test', 1)38 lab_template = create_lab_test_template()39 lab_test = create_lab_test(lab_template)40 lab_test.descriptive_test_items[0].result_value = 1241 lab_test.descriptive_test_items[1].result_value = 142 lab_test.descriptive_test_items[2].result_value = 2.343 lab_test.save()44 # check sample collection created45 self.assertTrue(frappe.db.exists('Sample Collection', {'sample': lab_template.sample}))46 frappe.db.set_value('Healthcare Settings', 'Healthcare Settings', 'create_sample_collection_for_lab_test', 0)47 lab_test = create_lab_test(lab_template)48 lab_test.descriptive_test_items[0].result_value = 1249 lab_test.descriptive_test_items[1].result_value = 150 lab_test.descriptive_test_items[2].result_value = 2.3...

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lane_dataset_builder.py

Source:lane_dataset_builder.py Github

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1import os2import time3import eyes4import controller as gamepad5import motor6import random7# Root path for train and test data8root = "images/lanes/"9# Controls motors based on curr_input and returns drive state10def controller_input_handler(curr_input, motor_control: motor):11 # If the start button is pressed:12 # Stop the training session and turn off motors13 if curr_input == "START":14 if motor_control.motor_state is True:15 motor_control.toggle_motor()16 return False # Ends the training loop17 # Drive motor using curr_input18 if curr_input == "A":19 motor_control.toggle_motor()20 if curr_input == "UP":21 motor_control.forward()22 if curr_input == "DOWN":23 motor_control.backward()24 if curr_input == "LEFT":25 motor_control.turn_left()26 if curr_input == "RIGHT":27 motor_control.turn_right()28 if curr_input == "LEFT TRIGGER":29 motor_control.rotate_left()30 if curr_input == "RIGHT TRIGGER":31 motor_control.rotate_right()32 drive_label = motor_control.get_drive_state_label()33 # DEBUG OUTPUT34 if curr_input is not None:35 print(f'{curr_input}\t--->\t{drive_label}')36 return drive_label37# Creates motor state directories if missing38def data_dir_check(path):39 if not os.path.exists(path):40 os.makedirs(path, exist_ok=True)41# Collects CNN training data:42# User input is read in a loop which controls the motor.43# The current drive state will be saved to the corresponding folder44# which can then be used to train the CNNmodel.45def collect_train_data(test_sample_collection=False):46 # Initialize movement counter47 drive_state_counter = {48 "stopped": 0, "forward": 0, "backward": 0,49 "left": 0, "right": 0,50 "rotate_right": 0, "rotate_left": 051 }52 motor_state = True53 # If test_sample_collection is enabled (TRUE),54 # ask for user input to determine what percent55 # of sampled data should be saved to the test data set56 if test_sample_collection:57 sample_percent = int(input("\nEnter percent of samples to save for testing pool:\n>> "))58 else:59 sample_percent = 060 # Initialize input device61 input_device = gamepad.Controller(3)62 # Initialize motor controller63 driver = motor.MotorControl()64 driver.set_speed(1) # Set drive speed to MIN65 # Initialize train/test data path66 train_save_path = os.path.join(root, 'train')67 test_save_path = os.path.join(root, 'test')68 save_path = train_save_path # Default save path69 data_dir_check(train_save_path)70 data_dir_check(train_save_path)71 # Initialize camera controller72 camera = eyes.Eyes()73 start_time = time.time()74 milli_sec_counter = time.time_ns()75 try:76 camera.camera_warm_up()77 while motor_state:78 curr_input = input_device.read_command()79 motor_state = controller_input_handler(curr_input, driver)80 if (motor_state != "stopped") \81 and (motor_state != "backward") \82 and (motor_state is not False):83 # If sampling enabled by user:84 # swap directory path between test and train85 # within desired percentage (sample_percent).86 if test_sample_collection:87 if random.randrange(0, 100 + 1) < sample_percent:88 save_path = test_save_path89 else:90 save_path = train_save_path91 # Set image name and path92 img_name = str(time.time_ns()) + ".png"93 img_path = os.path.join(save_path, motor_state)94 img_save_path = os.path.join(img_path, img_name)95 # Add delay between image captures to avoid data flooding96 # Save a forward image once every half second (1ms == 1^(6)ns)97 if motor_state == "forward":98 if (time.time_ns() - milli_sec_counter) > 500000000:99 camera.get_thresh_img()100 data_dir_check(img_path)101 camera.save_thresh_img(img_save_path)102 drive_state_counter[motor_state] += 1103 milli_sec_counter = time.time_ns()104 else:105 # Save an image once every quarter second106 if (time.time_ns() - milli_sec_counter) > 100000000:107 camera.get_thresh_img()108 data_dir_check(img_path)109 camera.save_thresh_img(img_save_path)110 drive_state_counter[motor_state] += 1111 milli_sec_counter = time.time_ns()112 except KeyboardInterrupt:113 print("\nInterrupt detected. Operation stopped.\n")114 except TypeError as e:115 print("\nTypeError:", e)116 except AssertionError as e:117 print(e)118 # Run device destructors119 motor.destroy()120 input_device.kill_device()121 camera.destroy()122 # Print elapsed train time123 print(f'\nCompleted Data Collection.')124 print(f'\tElapsed Time: {round(((time.time()-start_time)/60), 2)} minutes')125 # Print tally of saved images from session126 print('\n-----------------')127 for drive_state_lbl, count in drive_state_counter.items():128 print(f'{drive_state_lbl}:', count)129 print('-----------------')130if __name__ == '__main__':131 # ### Collect Train Data132 # Ask user for test data sampling133 enable_sampling = input("\nEnable train data sampling (y/n)?\n>> ")134 if enable_sampling.lower() == 'yes' or enable_sampling.lower() == 'y':135 enable_sampling = True136 else:137 enable_sampling = False138 # Start train data collection...

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