Add training script

Training/train.sh

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+#!/bin/bash
+
+########### SUDO COMMANDS WITHOUT PASSWORD #############################################
+# 
+# Specific commands must be executable without sudo
+# 
+# Add to sudoers file (sudo visudo):
+# 
+# Disable password for specific commands
+# pi ALL=(ALL:ALL) NOPASSWD: /usr/bin/chmod -R 755 /data/public/capserver/images
+# pi ALL=(ALL:ALL) NOPASSWD: /usr/bin/mv /home/pi/classifier.mlmodel /data/public/capserver/
+# pi ALL=(ALL:ALL) NOPASSWD: /usr/bin/mv /home/pi/classifier.version /data/public/capserver/
+# pi ALL=(ALL:ALL) NOPASSWD: /usr/bin/chown -R www-data\:www-data /data/public/capserver/
+#
+########################################################################################
+
+########### EXPLANATION OF RSYNC FLAGS #################################################
+# 
+# -h human readable output
+# -v verbose output
+# -r recursive
+# -P print information about long-running transfers, keep partial files (—-progress --partial)
+# -t preserves modification times
+# -u only update if newer
+# 
+########################################################################################
+
+########### PATHS ######################################################################
+
+WORK_DIR="/Users/imac/Projects/CapCollectorData"
+BACKUP_DIR="${WORK_DIR}/Backup"
+IMAGE_DIR="${WORK_DIR}/images"
+VERSION_FILE="${WORK_DIR}/classifier.version"
+MODEL_FILE="${WORK_DIR}/classifier.mlmodel"
+
+TRAINING_ITERATIONS="17"
+SSH_PORT="5432"
+SERVER="pi@pi4"
+SERVER_ROOT_PATH="/data/public/capserver"
+
+########################################################################################
+
+echo "[INFO] Working in directory ${WORK_DIR}"
+
+echo "[INFO] Getting classifier version from server..."
+scp -P $SSH_PORT ${SERVER}:/${SERVER_ROOT_PATH}/classifier.version $WORK_DIR
+
+# Read classifier version from file
+OLD_VERSION=$(< $VERSION_FILE)
+NEW_VERSION=$(($OLD_VERSION + 1))
+echo "[INFO] Creating classifier version ${NEW_VERSION}" 
+
+echo "[INFO] Ensuring permissions for images on server..."
+ssh -p $SSH_PORT ${SERVER} "sudo chmod -R 755 ${SERVER_ROOT_PATH}/images"
+
+echo "[INFO] Transferring images from server..."
+rsync -hvrPut -e "ssh -p ${SSH_PORT}" ${SERVER}:/${SERVER_ROOT_PATH}/images/ "${IMAGE_DIR}"
+
+echo "[INFO] Training the model..."
+swift train.swift $IMAGE_DIR $TRAINING_ITERATIONS $MODEL_FILE
+
+echo "[INFO] Backing up model..."
+cp $MODEL_FILE "${BACKUP_DIR}/classifier${NEW_VERSION}.mlmodel"
+
+echo "[INFO] Incrementing version file..."
+echo "${NEW_VERSION}" > $VERSION_FILE
+
+echo "[INFO] Copying the files to the server..."
+scp -P $SSH_PORT $MODEL_FILE $VERSION_FILE ${SERVER}:~/
+
+echo "[INFO] Moving files into public directory..."
+ssh -p ${SSH_PORT} ${SERVER} "sudo mv /home/pi/classifier.* ${SERVER_ROOT_PATH}/"
+
+echo "[INFO] Updating permissions..."
+ssh -p ${SSH_PORT} ${SERVER} "sudo chown -R www-data\:www-data ${SERVER_ROOT_PATH}/"
+
+echo "[INFO] Cleaning up..."
+rm $MODEL_FILE $VERSION_FILE
+
+echo "[INFO] Process finished"

Training/train.swift

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+import Cocoa
+import CreateML
+
+let defaultIterations = 17
+let defaultWorkingDirectory = URL(fileURLWithPath: "/Users/imac/Development/CapCollectorData")
+let defaultTrainDirectory = defaultWorkingDirectory.appendingPathComponent("images")
+let defaultClassifierFile = defaultWorkingDirectory.appendingPathComponent("classifier.mlmodel")
+
+func readArguments() -> (images: URL, classifier: URL, iterations: Int) {
+    let count = CommandLine.argc
+    guard count > 1 else {
+        // No arguments
+        return (defaultTrainDirectory, defaultClassifierFile, defaultIterations)
+    }
+    // First argument is the image directory
+    let imageDir = URL(fileURLWithPath: CommandLine.arguments[1])
+    let classifier = imageDir.deletingLastPathComponent().appendingPathComponent("classifier.mlmodel")
+    guard count > 2 else {
+        // Single argument is the image directory
+        return (imageDir, classifier, defaultIterations)
+    }
+    // Second argument is the iteration count
+    guard let iterations = Int(CommandLine.arguments[2]) else {
+        print("[ERROR] Invalid iterations argument '\(CommandLine.arguments[2])'")
+        exit(-1)
+    }
+    guard count > 3 else {
+        return (imageDir, classifier, iterations)
+    }
+    // Third argument is the classifier path
+    let classifierPath = URL(fileURLWithPath: CommandLine.arguments[3])
+    if count > 4 {
+        print("[WARNING] Ignoring additional arguments")
+    }
+    return (imageDir, classifierPath, iterations)
+}
+
+let arguments = readArguments()
+
+print("[INFO] Using images in \(arguments.images.path)")
+print("[INFO] Training for \(arguments.iterations) iterations")
+print("[INFO] Classifier path set to \(arguments.classifier.path)")
+
+var params = MLImageClassifier.ModelParameters(augmentation: [])
+params.maxIterations = arguments.iterations
+
+let model = try MLImageClassifier(
+    trainingData: .labeledDirectories(at: arguments.images),
+    parameters: params)
+
+print("[INFO] Writing classifier...")
+try model.write(to: arguments.classifier)
+
+/*
+let evaluation = model.evaluation(on: .labeledDirectories(at: trainDirectory))
+print("Printing evaluation:")
+print(evaluation)
+print("Finished evaluation")
+ */
+
+