Merge branch 'main' of https://whale.am28.uni-tuebingen.de/git/jgrewe/fixtracks

fixtracks/read_tracks.py

@@ -0,0 +1,76 @@
+import json
+import cv2 as cv
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+from IPython import embed
+
+def show_video(filename):
+    cap = cv.VideoCapture('2024.11.13_0_converted_right_undistorted_fixed.mp4')
+    count = 0
+    while cap.isOpened():
+        ret, frame = cap.read()
+        # if frame is read correctly ret is True
+        if not ret:
+            print("Can't receive frame (stream end?). Exiting ...")
+            break
+        count += 1
+        if count < 2000:
+            continue
+        gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
+        print(count)
+        cv.imshow('frame', gray[::2,::2])
+        if cv.waitKey(1) == ord('q'):
+            break
+    cap.release()
+    cv.destroyAllWindows()
+
+def topandas(filename):
+    temp = []
+    tracking_data = {"frame": [], "name": [], "cls": [],
+                     "confidence": [], "visible": [] ,
+                     "track_id": [],
+                     }
+    key_dict = {f"key_{i}": [] for i in range(6)}
+    box_labels =  ["x1", "y1", "x2", "y2"]
+    box_dict = {f"box_{i}": [] for i in box_labels}
+    tracking_data.update(key_dict)
+    tracking_data.update(box_dict)
+    
+    with open(filename, "r") as f:
+        data = json.load(f)
+    for d in data:  # each of the frames
+        if len(d["data"]) == 0:
+            continue
+        for dd in d["data"]:  # each of the found objects, i.e. fish
+            key_x = [float(x) for x in list(np.round(dd["keypoints"]["x"], 2))]
+            key_y = [float(y) for y in list(np.round(dd["keypoints"]["y"], 2))]
+            key_dict = {f"key_{i}": [v] for i, v in enumerate(zip(key_x, key_y))}
+            visible = np.round(dd["keypoints"]["visible"], 3)
+            tracking_data["frame"].append(d["frame"])
+            tracking_data["name"].append(dd["name"])
+            tracking_data["cls"].append(dd["class"])
+            tracking_data["visible"].append(visible)
+            tracking_data["confidence"].append(float(np.round(dd["confidence"], 3)))
+            tracking_data["track_id"].append(dd["track_id"] if "track_id" in dd.keys() else -1)
+            for bk, bl in zip(box_dict.keys(), box_labels):
+                tracking_data[bk].append(dd["box"][bl])
+            for i, kd in enumerate(key_dict.keys()):
+                tracking_data[kd].append((key_x[i], key_y[i]))
+            
+    df = pd.DataFrame(tracking_data)
+    return df
+
+def main():
+    # import left and right tracks into a pandas dataframe
+    right_tracks = "2024.11.13_0_converted_right_undistorted_fixed_pose.json"
+    left_tracks = "2024.11.13_0_converted_left_undistorted_fixed_pose.json"
+
+    rdf = topandas(right_tracks)
+    rdf.to_csv("right_tracks.csv", sep=";")
+    ldf = topandas(left_tracks)
+    ldf.to_csv("left_tracks.csv", sep=";")
+
+if __name__ == "__main__":
+    main()

resources.qrc

@@ -4,7 +4,10 @@
         <file alias="help">icons/help.png</file>
         <file alias="quit">icons/quit.png</file>
         <file alias="close">icons/nix_close.png</file>
-        <file alias="open">icons/nix_open.png</file>
+        <file alias="open">icons/open.png</file>
+        <file alias="merge">icons/merge.png</file>
+        <file alias="convert">icons/convert.png</file>
+        <file alias="tracks">icons/tracks.png</file>
         <file alias="settings">icons/settings.png</file>
     </qresource>
 </RCC>