Update example files

process_mating.py

@@ -29,6 +29,8 @@ img_process.update_leading_zero = False
 img_process.init_paths_names()
 img_process.max_diff_date_s = 90
 
+img_process.show_plot = False
+
 # # Fill dict with name of recordings to process
 # # > either all recordings from a given date
 # date_to_process = '20200303'
@@ -36,25 +38,77 @@ img_process.max_diff_date_s = 90
 # for camn in range(1, img_process.nb_cam + 1):
 #     rec_names_to_process[camn] = [s for s in img_process.all_folders_rec_cam[camn] if date_to_process in s]
 
+# > all recordings
 rec_names_to_process = {}
 for camn in range(1, img_process.nb_cam + 1):
     rec_names_to_process[camn] = img_process.all_folders_rec_cam[camn]
 
-img_process.show_plot = False
-
-# Convert image to 8 bits and reduce framerate (save in cam_save_paths/_Sample)
-img_process.do_batch('sample', rec_names=rec_names_to_process, step_frame=10, delete_previous=True)
 
-#img_process.do_batch('save_avi', from_fn_name='sample', delete_previous=True)
+# # Keep only rec_names that haven't been processed yet
+# non_processed_rec_names = {1: [], 2: [], 3: []}
+# for camn in range(1, img_process.nb_cam + 1):
+#     for i, rec_name in enumerate(rec_names_to_process[camn]):
+#         if not os.path.exists(os.path.join(img_process.cam_save_paths[camn], '_Avi', rec_name)):
+#             non_processed_rec_names[camn].append(rec_names_to_process[camn][i])
+#
+# rec_names_to_process = non_processed_rec_names
 
-# Enhance images (increase sharpness and contrast)
-# img_process.do_batch('autocontrast', rec_names=rec_names_to_process, from_fn_name='sample', delete_previous=True)
 
-# Do 2d tracking (blob detection) on images in cam_save_paths/_Sample
-# img_process.do_batch('track2d', rec_names=rec_names_to_process, from_fn_name='autocontrast')
+# -----------------------------------------------------------------------------------------------------------------------
+# Will prepare recordings to be used by Deeplabcut
 
+# > do everything automatically use 'multi_processes'
 # Do cropping, rotating, stitching, etc at once and save as .avi (save much time and space)
-# img_process.do_batch('multi_processes', rec_names=rec_names_to_process, yaml_path='processes.yaml', delete_previous=True)
-
-print('> All processes as been processed (total time elapsed: {0:.4f} s)'.format(time.time() - start))
+img_process.do_batch('multi_processes', rec_names=rec_names_to_process, yaml_path='processes.yaml', delete_previous=True)
 
+# > OR do each step separately
+# Convert image to 8 bits and reduce framerate (save in cam_save_paths/_Sample)
+# img_process.do_batch('sample', rec_names=rec_names_to_process, step_frame=50, delete_previous=True)
+#
+# # Do 2d tracking (blob detection) on images in cam_save_paths/_Sample
+# img_process.do_batch('track2d', rec_names=rec_names_to_process, from_fn_name='sample')
+#
+# # Do 3d reconstruction of tracks
+# img_process.do_batch('recon3d', rec_names=rec_names_to_process, from_fn_name='sample')
+#
+# # Crop all frames and save in cam_save_paths/_Cropped
+# img_process.do_batch('crop', rec_names=rec_names_to_process, from_fn_name='sample', height_crop=200, width_crop=200, delete_previous=True)
+#
+# # Rotate view 2 (to always have piston coming from right side)
+# img_process.do_batch('rotate', rec_names=rec_names_to_process, from_fn_name='crop', camns=[2], degrees=270)
+#
+# # Stitch all views together and save in cam_save_paths/_Stitched
+# img_process.do_batch('stitch', rec_names=rec_names_to_process, from_fn_name='crop', delete_previous=True)
+
+
+# -----------------------------------------------------------------------------------------------------------------------
+# Run Deeplabcut analysis + Fit 3D skeleton to 2D coordinate from Deeplabcut
+
+dlc_cfg_path = '/home/user/Desktop/Antoine/_maDLC/config.yaml'
+
+shuffle = 31
+iteration = 70000
+model_name = 'DLC_resnet50_MatingKinematicsshuffle{0}_{1}'.format(shuffle, iteration)
+
+res_method = '3d'  # '2d', '3d' or '2d_geo'
+opt_method = 'leastsq'  # 'powell' or 'leastsq' or 'least_squares'
+body_param_names = ['yaw_a', 'pitch_a', 'roll_a', 'x_com', 'y_com', 'z_com']
+wing_param_names = ['stroke_a', 'deviation_a', 'rotation_a']
+
+
+# # Track features using DeepLabCut
+# img_process.do_batch('analyse_dlc', rec_names=rec_names_to_process, from_fn_name='save_avi', cfg_path=dlc_cfg_path,
+#                     shuffle=shuffle, trainingsetindex=0, batchsize=5, save_avi=False, model_name=model_name, delete_previous=True)
+
+# # Load (+ filtering and unscrambling) 2d coords from DLC + Reverse processes (unstitch, rotate back, uncrop) + Reconstruct 3d coord
+# img_process.do_batch('load_dlc', rec_names=rec_names_to_process, from_fn_name='analyse_dlc', model_name=model_name,
+#                       tracker_method='skeleton')
+
+# # Optimize fit of skeleton to find body and wings angles
+# img_process.multiprocessing = True
+# img_process.threshold_likelihood = 0.85
+# img_process.do_batch('fit_skeleton', rec_names=rec_names_to_process, from_fn_name='load_dlc', model_name=model_name,
+#                      csv_path=csv_wings_geo_path, body_param_names=body_param_names, wing_param_names=wing_param_names,
+#                      res_method=res_method, opt_method=opt_method)
+
+print('> All processes as been processed (total time elapsed: {0:.4f} s)'.format(time.time() - start))
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