#54 Added sensible target identifier and dump more metadata

odcl_node.py

@@ -77,8 +77,8 @@ def get_next_in_dir(datadir: Path, suffix: str, k=5):
 
     Returns
     -------
-    str
-        string with enumeration length k plus suffix
+    tuple(int, str)
+        integer, and len(k) string representation
     """
     # find length k collection of digits
     digit_re = k * [r"\d"]
@@ -97,28 +97,30 @@ def get_next_in_dir(datadir: Path, suffix: str, k=5):
                 max_num = current
 
     # return padded string
-    return str(max_num + 1).rjust(k, "0") + suffix
+    return max_num, str(max_num + 1).rjust(k, "0")
 
 
 if __name__ == "__main__":
     rospy.init_node("odcl_node", anonymous=True)
+    rospy.loginfo("Started ODCL node...")
+
     # odcl data dir is set to a rospy param
     data_dir = rospy.get_param("/odcl/odcldir", "~/odcldata")
     # make a folder with today's date
     data_dir = Path(data_dir).resolve() / datetime.date.today().strftime("%Y%m%d")
-    os.makedirs(data_dir, exist_ok=True)
     # make a directory to save raw images
-    raw_image_dir = data_dir / "rawimg"
+    raw_image_dir = data_dir / "raw"
     # make a directory to save cropped images
-    crp_image_dir = data_dir / "crpimg"
-    for dir in (raw_image_dir, crp_image_dir):
+    crp_image_dir = data_dir / "crop"
+    for dir in (data_dir, raw_image_dir, crp_image_dir):
         os.makedirs(dir, exist_ok=True)
 
     # save odcl data txtfile
-    odcl_data_num = get_next_in_dir(data_dir, "-data.csv")
-    odcl_data_file = data_dir / odcl_data_num + "-data.csv"
-    # write headers to file
-    headers = "frame_no,in-frame-no,img_path,score,class,shapecolor,lettercolor,latitude,longitude\n"
+    run_id, run_id_str = get_next_in_dir(data_dir, "-data.csv")
+    odcl_data_file = data_dir / str(run_id_str + "-data.csv")
+
+    # write CSV headers to file
+    headers = "run_id,frame_no,target_no,target_id,img_path,crop_path,score,class,shape_color,letter_color,latitude,longitude,inference_time\n"
     with open(odcl_data_file, "a") as f:
         f.write(headers)
 
@@ -131,34 +133,38 @@ def get_next_in_dir(datadir: Path, suffix: str, k=5):
     capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 3000)
     odcl_node = OdclNode(model_path, labels_path)
 
-    frameno = 0
+    frameno = 1
     while True:
         if capture.isOpened():
-            rospy.loginfo(f"New frame {frameno}")
-
             # read raw image from camera
             status, image_raw = capture.read()
 
+            # get frame number
+            frameno_str = str(frameno).rjust(5)
+            frame_id = run_id_str + "_" + frameno_str
+            rospy.loginfo(f"Captured Frame {frameno} with id {frame_id}")
+
             # save raw image and log
-            raw_img_path = str(
-                raw_image_dir / get_next_in_dir(raw_image_dir, suffix="-raw.jpg")
-            )
-            cv2.imwrite(raw_img_path)
-            rospy.loginfo(f"Raw image saved to {raw_img_path}")
+            raw_img_path = raw_image_dir / str(frame_id + ".jpg")
+            cv2.imwrite(raw_img_path, image_raw)
+            rospy.loginfo(f"\tRaw image saved: {raw_img_path}")
 
             # run the pipeline
+            t0 = time.time()
             targets = odcl_node.pipeline.run(
                 image_raw,
                 odcl_node.gps,
                 odcl_node.altitude,
                 quat=odcl_node.quat,
             )
+            # inference time in ms
+            inftime = (time.time() - t0) * 1000
 
-            rospy.loginfo("Performed inference on raw image.")
-            rospy.loginfo(f"Found {len(targets)} targets.")
-            frameno += 1
+            rospy.loginfo(f"\tPerformed inference on raw image, took {inftime}ms")
+            rospy.loginfo(f"\tFound {len(targets)} targets.")
 
             for i, target in enumerate(targets):
+                targetno = str(i).rjust(2)
                 # unpack target information
                 lat = target["lat"]
                 lon = target["lon"]
@@ -170,17 +176,23 @@ def get_next_in_dir(datadir: Path, suffix: str, k=5):
                 score = round(target["score"], 3)
 
                 # log to rospy
-                targetinfo = f"Target {i}/{len(targets)}: shape={shape} ({score*100}%), scolor={scolor}, lcolor={lcolor}, lat={lat}, lon={lon}"
+                targetinfo = f"\tTarget {targetno}/{len(targets)}: shape={shape} ({score*100}%), scolor={scolor}, lcolor={lcolor}, lat={lat}, lon={lon}"
                 rospy.loginfo(targetinfo)
 
+                # save cropped image with unique identifier
+                targetid = frame_id + "_" + targetno
+                crop_fname = crp_image_dir / str(targetid + "jpg")
+                cv2.imwrite(crop_fname, img)
+                rospy.loginfo("\tSaved cropped image to {crop_fname}")
+
                 # write to csv
-                targetcsvline = f"{frameno},{i},{raw_img_path},{score},{shape},{scolor},{lcolor},{lat},{lon}\n"
+                targetcsvline = f"{run_id},{frameno},{targetno},{targetid},"
+                targetcsvline += f"{raw_img_path},{crop_fname},"
+                targetcsvline += f"{score},{shape},{scolor},{lcolor},{lat},{lon},"
+                targetcsvline += f"{inftime}\n"
                 with open(odcl_data_file, "a") as f:
                     f.write(targetcsvline)
 
-                # save cropped image with unique identifier
-                frameno_str = str(frameno).rjust(5)
-                i_str = str(i).rjust(2)
-                identifier = odcl_data_num[:5] + frameno_str + i_str
-                crop_fname = crp_image_dir / str(identifier + "jpg")
-                cv2.imwrite(crop_fname, img)
+            rospy.loginfo("\tRecorded data to {odcl_data_file}")
+
+            frameno += 1