Research

tools/hud_icon_match.py

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+IN_BIN = r"K:\ghidra\Crusader_Decomp\binary\Crusader - No Remorse Memdump Weapons.bin"
+W,H = 1024,512
+# regions
+HUD_BOX = (80,44,360,92)  # left,top,right,bot
+VSTRIP_X0, VSTRIP_X1 = 956, 1023
+import os, sys
+with open(IN_BIN,'rb') as f:
+    data = f.read()
+count = min(len(data)//2, W*H)
+# build RGB rows
+rows = []
+for y in range(H):
+    row = []
+    for x in range(W):
+        i = y*W + x
+        if i < count:
+            off = i*2
+            val = data[off] | (data[off+1]<<8)
+            b = (val & 0x1F) << 3
+            g = ((val >>5) & 0x1F) << 3
+            r = ((val >>10) & 0x1F) << 3
+        else:
+            r=g=b=0
+        row.append((r,g,b))
+    rows.append(row)
+# extract HUD crop
+lx,ty,rx,by = HUD_BOX
+w = rx-lx; h = by-ty
+hud = [[rows[y][x] for x in range(lx,rx)] for y in range(ty,by)]
+# build mask for HUD
+hud_mask = [[(1 if any(ch!=0 for ch in hud[y][x]) else 0) for x in range(w)] for y in range(h)]
+# extract vstrip area and find blobs
+vx0,vx1 = VSTRIP_X0, VSTRIP_X1
+vw = vx1-vx0+1
+vrows = [[rows[y][x] for x in range(vx0,vx1+1)] for y in range(H)]
+# mask and flood-fill
+mask = [[1 if any(ch!=0 for ch in vrows[y][x]) else 0 for x in range(vw)] for y in range(H)]
+visited = [[0]*vw for _ in range(H)]
+from collections import deque
+blobs = []
+for y in range(H):
+    for x in range(vw):
+        if mask[y][x] and not visited[y][x]:
+            q=deque([(x,y)])
+            visited[y][x]=1
+            xs=[]; ys=[]
+            while q:
+                cx,cy=q.popleft()
+                xs.append(cx); ys.append(cy)
+                for dx,dy in ((1,0),(-1,0),(0,1),(0,-1)):
+                    nx,ny = cx+dx, cy+dy
+                    if 0<=nx<vw and 0<=ny<H and mask[ny][nx] and not visited[ny][nx]:
+                        visited[ny][nx]=1; q.append((nx,ny))
+            x0,x1 = min(xs), max(xs)
+            y0,y1 = min(ys), max(ys)
+            area = len(xs)
+            blobs.append((x0,y0,x1,y1,area))
+# sort blobs by y (top to bottom)
+blobs.sort(key=lambda b: b[1])
+print('Found', len(blobs), 'blobs in vstrip')
+for i,b in enumerate(blobs):
+    x0,y0,x1,y1,area = b
+    print(i, 'blob box (vstrip coords)=', (x0,y0,x1,y1), 'area=',area)
+# extract blob images
+def extract_from_rows(rr, x0,y0,x1,y1):
+    w = x1-x0+1; h = y1-y0+1
+    img = [[rr[y+y0][x+x0] for x in range(w)] for y in range(h)]
+    return img
+blob_imgs = [extract_from_rows(vrows, *b[:4]) for b in blobs]
+# template match each blob against hud with sliding window
+import math
+results = []
+for bi, img in enumerate(blob_imgs):
+    bh = len(img); bw = len(img[0])
+    if bh<4 or bw<4: continue
+    best = (1e12, -1,-1)
+    # convert flattened arrays for speed
+    tmpl = [c for row in img for px in row for c in px]
+    for y in range(0, h-bh+1):
+        for x in range(0, w-bw+1):
+            ssd=0
+            for j in range(bh):
+                for i in range(bw):
+                    r1,g1,b1 = img[j][i]
+                    r2,g2,b2 = hud[j+y][i+x]
+                    dr=r1-r2; dg=g1-g2; db=b1-b2
+                    ssd += dr*dr + dg*dg + db*db
+                    if ssd>best[0]: break
+                if ssd>best[0]: break
+            if ssd < best[0]: best = (ssd,x,y)
+    results.append((bi,bw,bh,best[0],best[1],best[2]))
+# sort by score
+results.sort(key=lambda x: x[3])
+print('\nTop matches:')
+for bi,bw,bh,ssd,x,y in results[:10]:
+    # compute HUD pixel coordinates and vram offsets
+    hud_x = lx + x; hud_y = ty + y
+    start_idx = hud_y*W + hud_x
+    end_idx = (hud_y+bh-1)*W + (hud_x + bw -1)
+    so = start_idx*2; eo = (end_idx+1)*2 -1
+    vb = blobs[bi]
+    v_x0 = vx0 + vb[0]; v_y0 = vb[1]; v_x1 = vx0 + vb[2]; v_y1 = vb[3]
+    print(f'blob#{bi} vbox=({v_x0},{v_y0})-({v_x1},{v_y1}) size={bw}x{bh} bestssd={ssd} hudpos=({hud_x},{hud_y}) bytes=0x{so:06x}-0x{eo:06x}')
+
+# If results empty, report
+if not results:
+    print('No matches found')