hi, everyone i trained a model for image classification and it worked well on openmv using portenta h7 with portenta vision shield, i wanted to store the labels in a text file in the sd card but it is showing me the error.
import sensor, image, time, os, tf sensor.reset() # Reset and initialize the sensor. sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to RGB565 (or GRAYSCALE) sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240) sensor.set_windowing((240, 240)) # Set 240x240 window. sensor.skip_frames(time=2000) # Let the camera adjust. net = "trained.tflite" labels = [line.rstrip('\n') for line in open("labels.txt")] # Open a file in write mode to store the predicted labels with open('/sd/predictions.txt', 'w') as f: f.write("Predicted Labels:\n") clock = time.clock() while(True): clock.tick() img = sensor.snapshot() # default settings just do one detection... change them to search the image... for obj in tf.classify(net, img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5): print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect()) img.draw_rectangle(obj.rect()) # This combines the labels and confidence values into a list of tuples predictions_list = list(zip(labels, obj.output())) for i in range(len(predictions_list)): confidence = predictions_list[i] label = predictions_list[i] print("%s = %f" % (label, confidence)) # Write the predicted label to the file if the confidence is above 0.9 and the label is not "unknown" if confidence > 0.9 and label != "unknown": with open('/sd/predictions.txt', 'a') as f: f.write(label + "\n") print("It's a", label, "!") print(clock.fps(), "fps")
but it giving me the OSError: [Errno 2] ENOENT at " with open(‘/sd/predictions.txt’, ‘a’) as f: " this line.