Add script to run sai-cli without installation

python/cli/calibrate/calibrate.py

@@ -14,6 +14,9 @@ def define_subparser(subparsers):
     sub = subparsers.add_parser('calibrate', help=__doc__.strip())
     sub.set_defaults(func=call_calibrate)
     from spectacularAI.calibration import define_args as define_args_calibration
-    from .report import define_args as define_args_report
-    define_args_calibration(sub)
-    define_args_report(sub)
+    try:
+        from .report import define_args as define_args_report
+        define_args_calibration(sub)
+        define_args_report(sub)
+    except:
+        pass

python/cli/diagnose/diagnose.py

@@ -6,8 +6,8 @@
 import pathlib
 import sys
 
-from html1 import generateHtml
-import sensors
+from .html import generateHtml
+from .sensors import *
 
 def define_args(parser):
     parser.add_argument("dataset_path", type=pathlib.Path, help="Path to dataset")
@@ -128,12 +128,12 @@ def addMeasurement(type, t, v):
         if nSkipped > 0:
             print('skipped %d lines' % nSkipped)
 
-    sensors.camera(data, output)
-    sensors.accelerometer(data, output)
-    sensors.gyroscope(data, output)
-    sensors.magnetometer(data, output)
-    sensors.barometer(data, output)
-    sensors.cpu(data, output)
+    diagnoseCamera(data, output)
+    diagnoseAccelerometer(data, output)
+    diagnoseGyroscope(data, output)
+    diagnoseMagnetometer(data, output)
+    diagnoseBarometer(data, output)
+    diagnoseCpu(data, output)
 
     if args.output_json:
         with open(args.output_json, "w") as f:
@@ -150,4 +150,4 @@ def parse_args():
         parser = define_args(parser)
         return parser.parse_args()
 
-    generateReport(parse_args())
+    generateReport(parse_args())

python/cli/diagnose/sensors.py

@@ -186,7 +186,7 @@ def plotFrame(
 
     return base64(fig)
 
-def camera(data, output):
+def diagnoseCamera(data, output):
     data = data["cameras"]
     output["cameras"] = []
 
@@ -232,7 +232,7 @@ def camera(data, output):
                 **SIGNAL_PLOT_KWARGS))
         output["cameras"].append(cameraOutput)
 
-def accelerometer(data, output):
+def diagnoseAccelerometer(data, output):
     data = data["accelerometer"]
     timestamps = np.array(data["t"])
     deltaTimes = np.array(data["td"])
@@ -272,7 +272,7 @@ def accelerometer(data, output):
     if status.diagnosis == DiagnosisLevel.ERROR:
         output["passed"] = False
 
-def gyroscope(data, output):
+def diagnoseGyroscope(data, output):
     data = data["gyroscope"]
     timestamps = np.array(data["t"])
     deltaTimes = np.array(data["td"])
@@ -312,7 +312,7 @@ def gyroscope(data, output):
     if status.diagnosis == DiagnosisLevel.ERROR:
         output["passed"] = False
 
-def magnetometer(data, output):
+def diagnoseMagnetometer(data, output):
     data = data["magnetometer"]
     timestamps = np.array(data["t"])
     deltaTimes = np.array(data["td"])
@@ -352,7 +352,7 @@ def magnetometer(data, output):
     if status.diagnosis == DiagnosisLevel.ERROR:
         output["passed"] = False
 
-def barometer(data, output):
+def diagnoseBarometer(data, output):
     data = data["barometer"]
     timestamps = np.array(data["t"])
     deltaTimes = np.array(data["td"])
@@ -391,7 +391,7 @@ def barometer(data, output):
     if status.diagnosis == DiagnosisLevel.ERROR:
         output["passed"] = False
 
-def cpu(data, output):
+def diagnoseCpu(data, output):
     data = data["cpu"]
     timestamps = np.array(data["t"])
     values = data["v"]
@@ -400,4 +400,4 @@ def cpu(data, output):
 
     output["cpu"] = {
         "image": plotFrame(timestamps, values, "CPU system load (%)", ymin=0, ymax=100)
-    }
+    }

python/run_sai_cli.py

@@ -0,0 +1,4 @@
+from cli.sai_cli import main
+
+if __name__ == '__main__':
+    main()