update,

2025-01-31 22:56:58 +08:00
parent 57c7fd9332
commit b1cd1d4662
26 changed files with 6436 additions and 0 deletions
--- a/vinniesniper-54816/task1/_lab/001-test-integration/test_parameters.py
+++ b/vinniesniper-54816/task1/_lab/001-test-integration/test_parameters.py
@@ -0,0 +1,107 @@
+import os, sys
+import numpy as np
+from pprint import pprint
+
+np_raw_results_csv = np.genfromtxt(
+    "np_raw_results.csv",
+    delimiter=",",
+    dtype=[
+        ("img_test_path", "U50"),
+        ("diff_gray", "f8"),
+        ("diff_rgb", "f8"),
+        ("sift_match", "f8"),
+        ("diff_contour", "f8"),
+        ("d_cld_full", "f8"),
+        ("d_cld_up", "f8"),
+        ("d_cld_down", "f8"),
+        ("d_cld_left", "f8"),
+        ("d_cld_right", "f8"),
+    ],
+)
+
+
+np_raw_results = np.array([list(row) for row in np_raw_results_csv])
+pprint(np_raw_results)
+
+
+weight_diff_gray = 0.5
+weight_diff_rgb = 0.5
+weight_diff_sift = 0
+weight_diff_contour = 0
+weight_diff_cld = 0
+
+weight_diff_u = 0
+weight_diff_d = 0
+weight_diff_l = 0
+weight_diff_r = 0
+
+
+min_values = np.min(np_raw_results[:, 1:].astype(np.float64), axis=0)
+max_values = np.max(np_raw_results[:, 1:].astype(np.float64), axis=0)
+normalized_array = (np_raw_results[:, 1:].astype(np.float64) - min_values) / (max_values - min_values)
+np_raw_results = np.concatenate((np_raw_results, normalized_array), axis=1)
+
+start_col = 9
+np_raw_results[:, start_col + 1] = np_raw_results[:, start_col + 1].astype(np.float64) * weight_diff_gray
+
+np_raw_results[:, start_col + 2] = np_raw_results[:, start_col + 2].astype(np.float64) * weight_diff_rgb
+np_raw_results[:, start_col + 3] = (1 - np_raw_results[:, start_col + 3].astype(np.float64)) * weight_diff_sift
+np_raw_results[:, start_col + 4] = np_raw_results[:, start_col + 4].astype(np.float64) * weight_diff_contour
+#
+np_raw_results[:, start_col + 5] = np_raw_results[:, start_col + 5].astype(np.float64) * weight_diff_cld
+np_raw_results[:, start_col + 6] = np_raw_results[:, start_col + 6].astype(np.float64) * weight_diff_u
+np_raw_results[:, start_col + 7] = np_raw_results[:, start_col + 7].astype(np.float64) * weight_diff_d
+np_raw_results[:, start_col + 8] = np_raw_results[:, start_col + 8].astype(np.float64) * weight_diff_l
+np_raw_results[:, start_col + 9] = np_raw_results[:, start_col + 9].astype(np.float64) * weight_diff_r
+
+
+diff_sums = np.sum(np_raw_results[:, 10:-1].astype(np.float64), axis=1)
+
+np_raw_results = np.concatenate((np_raw_results, diff_sums[:, np.newaxis]), axis=1)
+np_raw_results = np.concatenate(
+    (np_raw_results, np.array([row[0].replace("image.orig/", "")[0] for row in np_raw_results])[:, np.newaxis]), axis=1
+)
+np_raw_results = np.concatenate((np_raw_results, np_raw_results[:, 0][:, np.newaxis]), axis=1)
+
+np_raw_results_sorted = np_raw_results[np.argsort(np_raw_results[:, -3].astype(np.float64))]
+
+raw_results = np_raw_results_sorted.tolist()
+
+column_names = [
+    "img_test_path",
+    "diff_gray",
+    "diff_rgb",
+    "sift_match",
+    "diff_contour",
+    "d_cld_full",
+    "d_cld_up",
+    "d_cld_down",
+    "d_cld_left",
+    "d_cld_right",
+    #
+    "w_gray",
+    "w_rgb",
+    "w_sift_match",
+    "w_contour",
+    "w_cld_full",
+    "w_cld_up",
+    "w_cld_down",
+    "w_cld_left",
+    "w_cld_right",
+    "w_sum",
+    "category",
+    "image",
+]
+
+np.savetxt(
+    "np_raw_results_sorted.csv",
+    np_raw_results_sorted,
+    delimiter=",",
+    fmt="%s",
+    header=",".join(column_names),
+    comments="",
+)
+
+# np.savetxt("np_raw_results_sorted.csv", np_raw_results_sorted, delimiter=",", fmt="%f")
+
+print(np_raw_results)