Warping code

example_dataset/F1P111_Vein_Center_200731_labels.json

@@ -13,7 +13,7 @@
                     "cy": 473
                 },
                 "region_attributes": {
-                    "label ": "center_vein_top"
+                    "label": "center_vein_top"
                 }
             },
             "1": {
@@ -23,7 +23,7 @@
                     "cy": 432
                 },
                 "region_attributes": {
-                    "label ": "center_vein_bottom"
+                    "label": "center_vein_bottom"
                 }
             }
         }

src/JSON_functions.py

@@ -43,11 +43,16 @@ def parse_annotation(image_name, project_dir, group_attr=None, id_attr=None):
         data_list = data[top_layer]['regions']
 
     for annotation in data_list:
+        #print(data_list)
         if group_attr: # if an attribute to group by is specified
             if (len(annotation['region_attributes']) == 0) and (len(data_list) == 1):
                 attr = "bounding_box"
             else:
-                attr = annotation['region_attributes'][group_attr]
+                #print("testing annotation['region_attributes']: ")
+                #print(annotation['region_attributes'])
+                #print(group_attr)
+                #print(filepath)
+                attr = annotation['region_attributes'][group_attr] #error spotted here
             if id_attr: # if an attribute to id by is specified
                 if attr not in new_dict.keys():
                     new_dict[attr] = {}
@@ -90,14 +95,17 @@ def img_crop(image_filename,file_path):
     '''
     #create full file routing information
     image_full = os.path.join(file_path,image_filename)
-    print(image_full)
+    #print(image_full)
     #read the image
-    img = cv.imread(image_full,cv.IMREAD_COLOR)
+    img = cv.imread(image_full,cv.IMREAD_COLOR) #think this is altering the colors.
+    #print('image type:', type(img))
+    #img = cv.UMat(img) #gpu acceleration
+    img = cv.cvtColor(img, cv.COLOR_BGR2RGB) #possible fix for color issue. fixed.
     assert not isinstance(img,type(None)), 'image not found'
 
     #Get Truncated Dictionary:
     new_dict = parse_annotation(image_filename,file_path, group_attr='label')
-    print(new_dict)
+    #print(new_dict)
     #Parse through each object's data for rectangle objects
     crop_key = 'bounding_box'
     if crop_key in new_dict:            
@@ -111,7 +119,6 @@ def img_crop(image_filename,file_path):
 
     else:
         raise ValueError("Image crop failed: \n  Annotation key " + crop_key + " not found in annotations file for " + image_filename)
-
     return croppedImg, new_dict
 
 
@@ -184,6 +191,15 @@ def main():
     for file in files:
         if not file.endswith("_labels.json"):
             print(parse_annotation(file, sys.argv[1], group_attr='label'), '\n')
+            img_crop(file, sys.argv[1])
+            print('\n')
+            '''
+            img = cv.imread(file, cv.IMREAD_COLOR)
+            display_annotations(parse_annotation(file, sys.argv[1], group_attr='label'), img)
+            print('\n')
+            '''
+
+
 
 #    img = cv.imread(image_filename,cv2.IMREAD_COLOR)
 #    cv.imshow('Image loaded with annotations layer applied!',img)
@@ -205,3 +221,6 @@ def main():
 
 #main()
 
+if __name__ == "__main__":
+    main()
+

src/LogReader.py

@@ -0,0 +1,101 @@
+import pandas as pd
+from pathlib import Path
+
+LOG_FILE = "cpu_profile_gpu_2.log"
+
+
+def load_log(logfile):
+    records = []
+
+    with open(logfile, "r", encoding="utf-8") as f:
+        for line in f:
+            line = line.strip()
+            if not line:
+                continue
+
+            parts = line.split(",")
+
+            timestamp = parts[0]
+            label = parts[1]
+
+            metrics = {}
+            for item in parts[2:]:
+                key, value = item.split("=")
+                metrics[key] = float(value)
+
+            records.append({
+                "timestamp": timestamp,
+                "label": label,
+                **metrics
+            })
+
+    df = pd.DataFrame(records)
+    df["timestamp"] = pd.to_datetime(df["timestamp"])
+    return df
+
+
+def summarize_by_label(df):
+    summary = (
+        df.groupby("label")
+        .agg(
+            calls=("wall", "count"),
+            wall_mean=("wall", "mean"),
+            wall_min=("wall", "min"),
+            wall_max=("wall", "max"),
+            cpu_mean=("cpu", "mean"),
+            cpu_max=("cpu", "max"),
+            user_mean=("user", "mean"),
+            sys_mean=("sys", "mean"),
+            cv_threads=("cv_threads", "max"),
+        )
+        .sort_values("wall_mean", ascending=False)
+    )
+
+    return summary
+
+
+def print_summary(summary):
+    pd.set_option("display.float_format", "{:.4f}".format)
+
+    print("\n=== CPU PROFILING SUMMARY (by label) ===\n")
+    print(summary)
+    print("\nLegend:")
+    print("  wall_*  : wall-clock seconds")
+    print("  cpu_*   : effective CPU utilization (%)")
+    print("  calls   : number of profiled invocations")
+    print("  cv_threads : OpenCV internal thread count\n")
+
+
+def detect_thread_changes(df):
+    changed = df[df["threads_start"] != df["threads_end"]]
+
+    if not changed.empty:
+        print("\n⚠ Thread count changed during profiling blocks:\n")
+        print(changed[[
+            "timestamp", "label",
+            "threads_start", "threads_end"
+        ]])
+    else:
+        print("\n✓ No thread count changes detected\n")
+
+
+def main():
+    logfile = Path(LOG_FILE)
+
+    if not logfile.exists():
+        raise FileNotFoundError(f"Log file not found: {logfile}")
+
+    df = load_log(logfile)
+
+    summary = summarize_by_label(df)
+    print_summary(summary)
+
+    detect_thread_changes(df)
+
+    # Optional CSV export for plotting
+    summary.to_csv("cpu_profile_summary.csv")
+    print("Summary written to cpu_profile_summary.csv")
+
+
+if __name__ == "__main__":
+    main()