55"colab" : {
66"provenance" : [],
77"mount_file_id" :" 1YJfEK8zha4PfUk2yP9y-XbO4vtmn83gE"
8- "authorship_tag" :" ABX9TyPqC8aZOBxrn5vwvNxHoub4 "
8+ "authorship_tag" :" ABX9TyPf94t3YgjtLkVRDYA222aU "
99"include_colab_link" :true
1010 },
1111"kernelspec" : {
107107" import os\n "
108108" import glob\n "
109109" import csv\n "
110- " import warnings"
110+ " import warnings\n "
111+ " from statistics import mode"
111112 ],
112113"metadata" : {
113114"id" :" whZwvEdKIksm"
278279"metadata" : {
279280"id" :" RHyJwan8acCz"
280281 },
281- "execution_count" :null ,
282+ "execution_count" :17 ,
282283"outputs" : []
283284 },
284285 {
297298 ],
298299"metadata" : {
299300"id" :" Zng2DvUJcJjc"
300- "outputId" :" 5e773745-adb7-45d0-fbf6-dc47ad96e633 "
301+ "outputId" :" 06119dd8-3a96-4a01-ef98-a102e9126ca7 "
301302"colab" : {
302303"base_uri" :" https://localhost:8080/"
303304 }
304305 },
305- "execution_count" :null ,
306+ "execution_count" :18 ,
306307"outputs" : [
307308 {
308309"name" :" stdout"
309310"output_type" :" stream"
310311"text" : [
311- " What model to use? heavy\n "
312+ " What model to use?(lite/heavy) heavy\n "
312313 ]
313314 }
314315 ]
332333" vid_path = root_path + '/Fit Form AI Resources/Videos/'"
333334 ],
334335"metadata" : {
335- "id" :" brFyKQV5aEuK"
336+ "id" :" brFyKQV5aEuK"
337+ "outputId" :" 29211e6f-c1d4-4e2c-dffe-618c5ebbab0e"
338+ "colab" : {
339+ "base_uri" :" https://localhost:8080/"
340+ }
336341 },
337- "execution_count" :null ,
338- "outputs" : []
342+ "execution_count" :19 ,
343+ "outputs" : [
344+ {
345+ "name" :" stdout"
346+ "output_type" :" stream"
347+ "text" : [
348+ " Would you like to record and save the video you create below? (Y / N)\n "
349+ " Y\n "
350+ ]
351+ }
352+ ]
339353 },
340354 {
341355"cell_type" :" code"
349363" if record:\n "
350364" out_video = cv.VideoWriter(vid_path + time.asctime(time.localtime()) + '.mp4',cv.VideoWriter_fourcc(*'DIVX'), 24, (640, 480))\n "
351365" landmarks_list = []\n "
352- " feedback_list = [\"\" ]\n "
366+ " feedback_list = []\n "
353367" selected_exercise = input(\" What exercise are you tracking?\\ n\" )\n "
354368" \n "
355369" \n "
371385" # print(\" Frame\" , timestamp_ms)\n "
372386" working_dstruct = lm_dstruct(landmarks_list[-1])\n "
373387" feedback_temp = working_dstruct.feedback(selected_exercise)\n "
374- " if feedback_list[-1] != feedback_temp:\n "
375- " print(feedback_temp)\n "
376388" feedback_list.append(feedback_temp)\n "
389+ " print(mode(feedback_list[-1:-4:-1]) if len(feedback_list) > 2 else feedback_temp)\n "
377390" if record:\n "
378391" out_video.write(annotated_image)\n "
379392" \n "
535548"outputs" : []
536549 }
537550 ]
538- }
551+ }