pippowell · feliciaelvina06 · Apr 2, 2024 · Apr 3, 2024 · Apr 8, 2024 · Apr 8, 2024
diff --git a/.gitignore b/.gitignore
@@ -139,4 +139,22 @@ dmypy.json
 ## Git
 .DS_Store
 
-/aibox/runs
+
+# Project specific directories and files
+aibox/resources/datasets/
+aibox/resources/old_code/Testing/
+aibox/resources/fruithands.csv
+aibox/resources/hands_fp_raw.csv
+aibox/resources/object_detector_idea.pdf
+aibox/example_gpu.sh
+aibox/UOS_HPC_Guide.md
+flobox/experiment/analysis/Ramon/
+flobox/experiment/forms/
+flobox/experiment/plots/
+flobox/experiment/Abrechnung_VPgelder.pdf
+flobox/experiment/Data_Analysis.zip
+flobox/resources/Copenhagen/
+flobox/resources/OptiVisT_Retreat_Poster.pdf
+flobox/resources/OptiVisT_Workshop_Program.pdf
+flobox/resources/OptiVisT_Workshop_Timetable.pdf
+flobox/Powell2024-Helping_Blind_People_Grasp.pdf
diff --git a/README.md b/README.md
@@ -38,3 +38,24 @@ You do not need all the YOLOv5 files, just the following:
 - export.py
 
 If you clone this repo, YOLOv5 is already set up properly and you only need to separately install the YOLOv8 packages into your environment.
+
+
+### Exporting models for use with the NLInterface Android App
+
+These models can be used in the Android app developed during the study project "Making blind people grasp" in 2023/2024 lead by Peter König.
+The script for that is located in `aibox/app_export.py` and works for the hand detection as well as object detection.
+
+To export the hand detection model, first export it as a tensorflow saved model using the default export script.
+
+```bash
+$ cd aibox
+$ python export.py --weights hand.pt --include saved_model --keras
+```
+This will create the `hand_saved_model` directory.
+
+After that you can convert it for the Tensorflow-Lite Runtime using
+
+```bash
+$ python app_export.py --hands hand_saved_model --output hands.tflite
+```
+To run the master.py file, change directory into the aibox folder before executing the code (pathing issue).
diff --git a/Shape_detection/Images/0.jpg b/Shape_detection/Images/0.jpg
diff --git a/Shape_detection/Images/1.jpg b/Shape_detection/Images/1.jpg
diff --git a/Shape_detection/Images/2.jpg b/Shape_detection/Images/2.jpg
diff --git a/Shape_detection/Images/3.jpg b/Shape_detection/Images/3.jpg
diff --git a/Shape_detection/Images/4.jpg b/Shape_detection/Images/4.jpg
diff --git a/Shape_detection/Images/5.jpg b/Shape_detection/Images/5.jpg
diff --git a/Shape_detection/Images/6.jpg b/Shape_detection/Images/6.jpg
diff --git a/Shape_detection/Images/7.jpg b/Shape_detection/Images/7.jpg
diff --git a/Shape_detection/Images/8.jpg b/Shape_detection/Images/8.jpg
diff --git a/Shape_detection/Images/9.jpg b/Shape_detection/Images/9.jpg
diff --git a/Shape_detection/Images/a.jpg b/Shape_detection/Images/a.jpg
diff --git a/Shape_detection/Images/b.jpg b/Shape_detection/Images/b.jpg
diff --git a/Shape_detection/Images/c.jpg b/Shape_detection/Images/c.jpg
diff --git a/Shape_detection/Images/d.jpg b/Shape_detection/Images/d.jpg
diff --git a/Shape_detection/Images/e.jpg b/Shape_detection/Images/e.jpg
diff --git a/Shape_detection/Images/emnist.zip b/Shape_detection/Images/emnist.zip
diff --git a/Shape_detection/Images/f.jpg b/Shape_detection/Images/f.jpg
diff --git a/Shape_detection/Images/g.jpg b/Shape_detection/Images/g.jpg
diff --git a/Shape_detection/Images/h.jpg b/Shape_detection/Images/h.jpg
diff --git a/Shape_detection/Images/i.jpg b/Shape_detection/Images/i.jpg
diff --git a/Shape_detection/Images/j.jpg b/Shape_detection/Images/j.jpg
diff --git a/Shape_detection/Images/k.jpg b/Shape_detection/Images/k.jpg
diff --git a/Shape_detection/Images/l.jpg b/Shape_detection/Images/l.jpg
diff --git a/Shape_detection/Images/m.jpg b/Shape_detection/Images/m.jpg
diff --git a/Shape_detection/Images/n.jpg b/Shape_detection/Images/n.jpg
diff --git a/Shape_detection/Images/p.jpg b/Shape_detection/Images/p.jpg
diff --git a/Shape_detection/Images/q.jpg b/Shape_detection/Images/q.jpg
diff --git a/Shape_detection/Images/r.jpg b/Shape_detection/Images/r.jpg
diff --git a/Shape_detection/Images/s.jpg b/Shape_detection/Images/s.jpg
diff --git a/Shape_detection/Images/t.jpg b/Shape_detection/Images/t.jpg
diff --git a/Shape_detection/Images/try.jpg b/Shape_detection/Images/try.jpg
diff --git a/Shape_detection/Images/u.jpg b/Shape_detection/Images/u.jpg
diff --git a/Shape_detection/Images/v.jpg b/Shape_detection/Images/v.jpg
diff --git a/Shape_detection/Images/w.jpg b/Shape_detection/Images/w.jpg
diff --git a/Shape_detection/Images/x.jpg b/Shape_detection/Images/x.jpg
diff --git a/Shape_detection/Images/y.jpg b/Shape_detection/Images/y.jpg
diff --git a/Shape_detection/Images/z.jpg b/Shape_detection/Images/z.jpg
diff --git a/Shape_detection/Participants/0/alpha intensity_0.txt b/Shape_detection/Participants/0/alpha intensity_0.txt
@@ -0,0 +1,5 @@
+int_top: 94
+int_bottom: 94
+int_left: 94
+int_right: 94
+avg_int: 94
diff --git a/Shape_detection/Participants/0/alpha training_0.txt b/Shape_detection/Participants/0/alpha training_0.txt
@@ -0,0 +1,13 @@
+Participant ID: 0
+Intensity for top and bottom: 94
+Intensity for right and left: 94
+Average intensity: 94
+Training task: 2 set/sets
+
+Set 1 block accuracies: [87.5, 62.5, 100.0]
+Set 1 average accuracy: 83.33%
+
+Set 2 block accuracies: [100.0, 81.25, 100.0]
+Set 2 average accuracy: 93.75%
+
+Overall training completed with an average accuracy of 88.54%
diff --git a/Shape_detection/Participants/0/alpha training_0.xlsx b/Shape_detection/Participants/0/alpha training_0.xlsx
diff --git a/Shape_detection/Participants/0/alpha_0_120.png b/Shape_detection/Participants/0/alpha_0_120.png
diff --git a/Shape_detection/Participants/0/alpha_cm_0_Set 1.png b/Shape_detection/Participants/0/alpha_cm_0_Set 1.png
diff --git a/Shape_detection/Participants/0/alpha_cm_0_Set 2.png b/Shape_detection/Participants/0/alpha_cm_0_Set 2.png
diff --git a/Shape_detection/Participants/0/beta intensity_0.txt b/Shape_detection/Participants/0/beta intensity_0.txt
@@ -0,0 +1,6 @@
+preference: Interval
+int_top: 83
+int_bottom: 83
+int_left: 83
+int_right: 83
+avg_int: 83
diff --git a/Shape_detection/Participants/0/beta training_0.txt b/Shape_detection/Participants/0/beta training_0.txt
@@ -0,0 +1,17 @@
+Participant ID: 0
+Diagonal pattern: Simultaneous
+Intensity for top and bottom: 83
+Intensity for right and left: 83
+Average intensity: 83
+Training task: 4 set/sets
+
+Set 1 block accuracies: [56.25, 62.5, 31.25]
+Set 1 average accuracy: 50.00%
+
+Set 2 block accuracies: [37.5, 43.75, 43.75]
+Set 2 average accuracy: 41.67%
+
+Set 3 block accuracies: [37.5, 43.75, 43.75]
+Set 3 average accuracy: 41.67%
+
+Overall training completed with an average accuracy of 44.44%
diff --git a/Shape_detection/Participants/0/beta training_0.xlsx b/Shape_detection/Participants/0/beta training_0.xlsx
diff --git a/Shape_detection/Participants/0/beta_0_60.png b/Shape_detection/Participants/0/beta_0_60.png
diff --git a/Shape_detection/Participants/0/beta_cm_0_Set 1.png b/Shape_detection/Participants/0/beta_cm_0_Set 1.png
diff --git a/Shape_detection/Participants/0/beta_cm_0_Set 2.png b/Shape_detection/Participants/0/beta_cm_0_Set 2.png
diff --git a/Shape_detection/Participants/0/beta_cm_0_Set 3.png b/Shape_detection/Participants/0/beta_cm_0_Set 3.png
diff --git a/Shape_detection/Participants/1/alpha intensity_1.txt b/Shape_detection/Participants/1/alpha intensity_1.txt
@@ -0,0 +1,5 @@
+int_top: 10
+int_bottom: 10
+int_left: 10
+int_right: 10
+avg_int: 10
diff --git a/Shape_detection/Participants/1/alpha order_1.txt b/Shape_detection/Participants/1/alpha order_1.txt
@@ -0,0 +1,30 @@
+
+Starting category: numbers
+7
+9
+6
+3
+0
+2
+1
+5
+8
+4
+
+Starting category: letters
+p
+d
+c
+j
+b
+s
+a
+e
+g
+l
+q
+h
+i
+u
+f
+t
diff --git a/Shape_detection/Participants/1/alpha training_1.txt b/Shape_detection/Participants/1/alpha training_1.txt
@@ -0,0 +1,13 @@
+Participant ID: 1
+Intensity for top and bottom: 10
+Intensity for right and left: 10
+Average intensity: 10
+Training task: 2 set/sets
+
+Set 1 block accuracies: [62.5, 87.5, 75.0]
+Set 1 average accuracy: 75.00%
+
+Set 2 block accuracies: [100.0, 100.0, 100.0]
+Set 2 average accuracy: 100.00%
+
+Overall training completed with an average accuracy of 87.50%
diff --git a/Shape_detection/Participants/1/alpha training_1.xlsx b/Shape_detection/Participants/1/alpha training_1.xlsx
diff --git a/Shape_detection/Participants/1/alpha_1_120.png b/Shape_detection/Participants/1/alpha_1_120.png
diff --git a/Shape_detection/Participants/1/alpha_1_60.png b/Shape_detection/Participants/1/alpha_1_60.png
diff --git a/Shape_detection/Participants/1/alpha_cm_1_Set 1.png b/Shape_detection/Participants/1/alpha_cm_1_Set 1.png
diff --git a/Shape_detection/Participants/1/alpha_cm_1_Set 2.png b/Shape_detection/Participants/1/alpha_cm_1_Set 2.png
diff --git a/Shape_detection/Participants/1/beta intensity_1.txt b/Shape_detection/Participants/1/beta intensity_1.txt
@@ -0,0 +1,6 @@
+preference: Interval
+int_top: 15
+int_bottom: 15
+int_left: 15
+int_right: 15
+avg_int: 15
diff --git a/Shape_detection/Participants/1/beta order_1.txt b/Shape_detection/Participants/1/beta order_1.txt
@@ -0,0 +1,41 @@
+
+Starting category: numbers
+7
+5
+1
+4
+9
+0
+8
+2
+3
+6
+
+Starting category: letters
+u
+i
+h
+q
+b
+p
+f
+e
+t
+l
+s
+d
+c
+a
+j
+g
+
+Starting category: beta
+z
+n
+x
+k
+w
+v
+r
+m
+y
diff --git a/Shape_detection/Participants/1/beta training_1.txt b/Shape_detection/Participants/1/beta training_1.txt
@@ -0,0 +1,11 @@
+Participant ID: 1
+Diagonal pattern: Interval
+Intensity for top and bottom: 15
+Intensity for right and left: 15
+Average intensity: 15
+Training task: 1 set/sets
+
+Set 1 block accuracies: [93.75, 93.75, 87.5]
+Set 1 average accuracy: 91.67%
+
+Overall training completed with an average accuracy of 91.67%
diff --git a/Shape_detection/Participants/1/beta training_1.xlsx b/Shape_detection/Participants/1/beta training_1.xlsx
diff --git a/Shape_detection/Participants/1/beta_1_60.png b/Shape_detection/Participants/1/beta_1_60.png
diff --git a/Shape_detection/Participants/1/beta_cm_1_Set 1.png b/Shape_detection/Participants/1/beta_cm_1_Set 1.png
diff --git a/Shape_detection/Participants/2/alpha intensity_2.txt b/Shape_detection/Participants/2/alpha intensity_2.txt
@@ -0,0 +1,5 @@
+int_top: 86
+int_bottom: 86
+int_left: 83
+int_right: 83
+avg_int: 84
diff --git a/Shape_detection/Participants/2/alpha order_2.txt b/Shape_detection/Participants/2/alpha order_2.txt
@@ -0,0 +1,30 @@
+
+Starting category: numbers
+8
+0
+5
+7
+1
+9
+4
+3
+2
+6
+
+Starting category: letters
+c
+b
+l
+u
+g
+q
+j
+p
+a
+s
+f
+d
+i
+h
+e
+t
diff --git a/Shape_detection/Participants/2/alpha training_2.txt b/Shape_detection/Participants/2/alpha training_2.txt
@@ -0,0 +1,16 @@
+Participant ID: 2
+Intensity for top and bottom: 86
+Intensity for right and left: 83
+Average intensity: 84
+Training task: 3 set/sets
+
+Set 1 block accuracies: [81.25, 62.5, 93.75]
+Set 1 average accuracy: 79.17%
+
+Set 2 block accuracies: [81.25, 100.0, 87.5]
+Set 2 average accuracy: 89.58%
+
+Set 3 block accuracies: [81.25, 93.75, 100.0]
+Set 3 average accuracy: 91.67%
+
+Overall training completed with an average accuracy of 86.81%
diff --git a/Shape_detection/Participants/2/alpha training_2.xlsx b/Shape_detection/Participants/2/alpha training_2.xlsx
diff --git a/Shape_detection/Participants/2/alpha_2_120.png b/Shape_detection/Participants/2/alpha_2_120.png
diff --git a/Shape_detection/Participants/2/alpha_2_60.png b/Shape_detection/Participants/2/alpha_2_60.png
diff --git a/Shape_detection/Participants/2/alpha_cm_2_Set 1.png b/Shape_detection/Participants/2/alpha_cm_2_Set 1.png
diff --git a/Shape_detection/Participants/2/alpha_cm_2_Set 2.png b/Shape_detection/Participants/2/alpha_cm_2_Set 2.png
diff --git a/Shape_detection/Participants/2/alpha_cm_2_Set 3.png b/Shape_detection/Participants/2/alpha_cm_2_Set 3.png
diff --git a/Shape_detection/Participants/2/beta intensity_2.txt b/Shape_detection/Participants/2/beta intensity_2.txt
@@ -0,0 +1,6 @@
+preference: Interval
+int_top: 94
+int_bottom: 94
+int_left: 94
+int_right: 94
+avg_int: 94
diff --git a/Shape_detection/Participants/2/beta order_2.txt b/Shape_detection/Participants/2/beta order_2.txt
@@ -0,0 +1,41 @@
+
+Starting category: numbers
+9
+4
+2
+1
+6
+5
+3
+8
+7
+0
+
+Starting category: letters
+i
+h
+b
+f
+t
+q
+d
+j
+g
+p
+c
+a
+l
+u
+s
+e
+
+Starting category: beta
+n
+v
+x
+y
+w
+z
+r
+k
+m
diff --git a/Shape_detection/Participants/2/beta training_2.txt b/Shape_detection/Participants/2/beta training_2.txt
@@ -0,0 +1,17 @@
+Participant ID: 2
+Diagonal pattern: Interval
+Intensity for top and bottom: 94
+Intensity for right and left: 94
+Average intensity: 94
+Training task: 4 set/sets
+
+Set 1 block accuracies: [68.75, 87.5, 81.25]
+Set 1 average accuracy: 79.17%
+
+Set 2 block accuracies: [62.5, 93.75, 31.25]
+Set 2 average accuracy: 62.50%
+
+Set 3 block accuracies: [75.0, 93.75, 87.5]
+Set 3 average accuracy: 85.42%
+
+Overall training completed with an average accuracy of 75.69%
diff --git a/Shape_detection/Participants/2/beta training_2.xlsx b/Shape_detection/Participants/2/beta training_2.xlsx
diff --git a/Shape_detection/Participants/2/beta_2_60.png b/Shape_detection/Participants/2/beta_2_60.png
diff --git a/Shape_detection/Participants/2/beta_cm_2_Set 1.png b/Shape_detection/Participants/2/beta_cm_2_Set 1.png
diff --git a/Shape_detection/Participants/2/beta_cm_2_Set 2.png b/Shape_detection/Participants/2/beta_cm_2_Set 2.png
diff --git a/Shape_detection/Participants/2/beta_cm_2_Set 3.png b/Shape_detection/Participants/2/beta_cm_2_Set 3.png
diff --git a/Shape_detection/Participants/3/alpha intensity_3.txt b/Shape_detection/Participants/3/alpha intensity_3.txt
@@ -0,0 +1,5 @@
+int_top: 87
+int_bottom: 87
+int_left: 87
+int_right: 87
+avg_int: 87
diff --git a/Shape_detection/Participants/3/alpha order_3.txt b/Shape_detection/Participants/3/alpha order_3.txt
@@ -0,0 +1,30 @@
+
+Starting category: numbers
+9
+1
+3
+0
+7
+5
+6
+4
+8
+2
+
+Starting category: letters
+i
+q
+t
+a
+g
+h
+l
+s
+u
+d
+j
+c
+f
+b
+e
+p
diff --git a/Shape_detection/Participants/3/alpha training_3.txt b/Shape_detection/Participants/3/alpha training_3.txt
@@ -0,0 +1,10 @@
+Participant ID: 3
+Intensity for top and bottom: 87
+Intensity for right and left: 87
+Average intensity: 87
+Training task: 1 set/sets
+
+Set 1 block accuracies: [100.0, 100.0, 100.0]
+Set 1 average accuracy: 100.00%
+
+Overall training completed with an average accuracy of 100.00%
diff --git a/Shape_detection/Participants/3/alpha training_3.xlsx b/Shape_detection/Participants/3/alpha training_3.xlsx
diff --git a/Shape_detection/Participants/3/alpha_3_60.png b/Shape_detection/Participants/3/alpha_3_60.png
diff --git a/Shape_detection/Participants/3/alpha_cm_3_Set 1.png b/Shape_detection/Participants/3/alpha_cm_3_Set 1.png
diff --git a/Shape_detection/Participants/3/beta intensity_3.txt b/Shape_detection/Participants/3/beta intensity_3.txt
@@ -0,0 +1,6 @@
+preference: Interval
+int_top: 89
+int_bottom: 89
+int_left: 91
+int_right: 91
+avg_int: 90