(file_path)
| 64 | return results |
| 65 | |
| 66 | def load_image_data(file_path): |
| 67 | with open(file_path, 'r') as file: |
| 68 | lines = file.readlines() |
| 69 | count = 0 |
| 70 | image_data = [] |
| 71 | for i in range(len(lines)): |
| 72 | line = lines[i].strip() |
| 73 | if line.startswith("#") or not line.strip(): |
| 74 | continue |
| 75 | count = count + 1 |
| 76 | if(count % 2 == 0): |
| 77 | continue |
| 78 | # IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME |
| 79 | parts = line.split() |
| 80 | image_id = int(parts[0]) # IMAGE_ID |
| 81 | qw, qx, qy, qz = map(float, parts[1:5]) # quat |
| 82 | tx, ty, tz = map(float, parts[5:8]) # trans |
| 83 | camera_id = int(parts[8]) # CAMERA_ID |
| 84 | name = parts[9] # IMAGE NAME |
| 85 | |
| 86 | pose = {"qw": qw, "qx": qx, "qy": qy, "qz": qz, "tx": tx, "ty": ty, "tz": tz} |
| 87 | image_data.append((name, image_id, camera_id, pose)) |
| 88 | |
| 89 | df = pd.DataFrame(image_data, columns=['NAME', 'IMAGE_ID', 'CAMERA_ID', 'POSE']) |
| 90 | df.set_index('NAME', inplace=True) |
| 91 | return df |
| 92 | |
| 93 | def load_gt_depth(gt_path): |
| 94 | image_path = gt_path + "/images.txt" |
no outgoing calls
no test coverage detected