import struct, math, numpy as np
from PIL import Image
data=open("content/VIDEO/GEO/BLX_COP.BGF","rb").read()
verts=[]; uvs=[]; faces=[]
cb=[0]
def addpoly(idx,b):
    for k in range(1,len(idx)-1): faces.append((b+idx[0],b+idx[k],b+idx[k+1]))
def parse(p,end):
    while p+3<=end:
        tw=struct.unpack_from("<H",data,p)[0]; p+=2
        cid=tw&0x2fff; lw=4 if(tw&0x8000)else(2 if(tw&0x4000)else 1)
        if p+lw>end:return
        ln=data[p] if lw==1 else(struct.unpack_from("<H",data,p)[0] if lw==2 else struct.unpack_from("<I",data,p)[0])
        p+=lw
        if p+ln>end:return
        if cid==0x88:
            cb[0]=len(verts)
            for i in range(ln//20):
                o=p+i*20; x,y,z=struct.unpack_from("<fff",data,o); u,v=struct.unpack_from("<ff",data,o+12)
                verts.append((x,y,z)); uvs.append((u,v))
        elif cid==0x47:
            n=ln//4; idx=[struct.unpack_from("<I",data,p+i*4)[0] for i in range(n)]
            for f in range(0,(n//3)*3,3): faces.append((cb[0]+idx[f],cb[0]+idx[f+1],cb[0]+idx[f+2]))
        elif cid==0x4d:
            if ln>=1:
                ppf=data[p]; n=(ln-1)//4
                idx=[struct.unpack_from("<I",data,p+1+i*4)[0] for i in range(n)]
                for f in range(0,(n//ppf)*ppf,ppf): addpoly([idx[f+j] for j in range(ppf)],cb[0])
        if cid in {0x3,0x70,0x40,0x41,0x42,0x46,0x48,0x10,0x20,0x30}: parse(p,p+ln)
        p+=ln
        if cid==0x5:break
parse(8,len(data))
V=np.array(verts); UV=np.array(uvs)
# classify each face: all-3-verts UV=(0,0) -> class0 (RED), else class1 (GREEN)
def cls(f):
    return 0 if all(abs(UV[i,0])<1e-4 and abs(UV[i,1])<1e-4 for i in f) else 1
c0=sum(1 for f in faces if cls(f)==0); c1=len(faces)-c0
print(f"faces total {len(faces)}: UV(0,0) faces={c0}  non-zero-UV faces={c1}")
# render both classes in distinct colors from a few eyepoints
def render(eye,look,fov=95,W=380,H=290):
    eye=np.array(eye,float);fwd=np.array(look,float)-eye;fwd/=np.linalg.norm(fwd)
    up=np.array([0,1,0.]);right=np.cross(fwd,up);right/=np.linalg.norm(right);upv=np.cross(right,fwd)
    f=(H/2)/math.tan(math.radians(fov)/2);img=np.zeros((H,W,3));zb=np.full((H,W),1e18)
    for face in faces:
        col=[0.9,0.15,0.15] if cls(face)==0 else [0.15,0.9,0.15]
        tri=V[list(face)]
        cam=[(np.dot(pt-eye,right),np.dot(pt-eye,upv),np.dot(pt-eye,fwd)) for pt in tri]
        if any(cz<=0.03 for _,_,cz in cam):continue
        pts=[(W/2+f*cx/cz,H/2-f*cy/cz,cz) for cx,cy,cz in cam]
        xs=[p[0] for p in pts];ys=[p[1] for p in pts]
        mnx=max(int(min(xs)),0);mxx=min(int(max(xs))+1,W-1);mny=max(int(min(ys)),0);mxy=min(int(max(ys))+1,H-1)
        if mnx>=mxx or mny>=mxy:continue
        (x0,y0,z0),(x1,y1,z1),(x2,y2,z2)=pts
        den=((y1-y2)*(x0-x2)+(x2-x1)*(y0-y2))
        if abs(den)<1e-9:continue
        ys2,xs2=np.mgrid[mny:mxy+1,mnx:mxx+1];xf=xs2+.5;yf=ys2+.5
        l0=((y1-y2)*(xf-x2)+(x2-x1)*(yf-y2))/den;l1=((y2-y0)*(xf-x2)+(x0-x2)*(yf-y2))/den;l2=1-l0-l1
        m=(l0>=0)&(l1>=0)&(l2>=0)
        z=l0*z0+l1*z1+l2*z2
        yi=ys2[m];xi=xs2[m];zz=z[m];cl_=zz<zb[yi,xi]
        zb[yi[cl_],xi[cl_]]=zz[cl_];img[yi[cl_],xi[cl_]]=col
    return (np.clip(img,0,1)*255).astype(np.uint8)
cen=V.mean(0)
tiles=[render(cen.tolist(),(cen+[0,0,-30]).tolist()),
       render(cen.tolist(),(cen+[0,0,30]).tolist()),
       render((0,-0.3,0),(0,-0.3,-4))]
Image.fromarray(np.concatenate(tiles,axis=1)).save("scratchpad/cop_split.png")
print("saved cop_split.png [RED=UV(0,0) faces, GREEN=non-zero-UV faces]")