Update handcrafted_solution.py

handcrafted_solution.py

@@ -373,13 +373,14 @@ def get_sparse_depth(colmap_rec, img_id, K, R, t, depth):
     xyz = []
     rgb = []
     found = False
-    print (img_id)
+    #print (img_id)
     for img_id_c, col_img in colmap_rec.images.items():
         print (col_img.name)
         if col_img.name == img_id:
             found = True
             break
     if not found:
+        print (f"{img_id} not found, returning empty depth")
         return np.zeros((H, W), dtype=np.float32), False
     mat4x4 = np.eye(4)
     mat4x4[:3 ] = col_img.cam_from_world.matrix()
@@ -435,10 +436,7 @@ def fit_scale_robust_median(depth, sparse_depth):
         k, b = params
         return np.median(np.abs(yvals - (k*xvals)))
 
-    # 3. Get an initial guess from a standard least-squares fit
-    #    (this helps the optimizer start in a reasonable region)
-    k_init, b_init = np.polyfit(X, Y, deg=1)
-
+    k_init, b_init = 1.0, 0.0
     # 4. Optimize using a derivative-free method (Nelder-Mead)
     res = minimize(
         fun=median_abs_resid,