Clustering scanner
Signed-off-by: James Ketrenos <james_gitlab@ketrenos.com>
This commit is contained in:
James Ketrenos
parent
f28293c3f1
commit
0ed48fd7f7
34
clusters-pre
Normal file
34
clusters-pre
Normal file
@ -0,0 +1,34 @@
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<html>
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<script>'<base href="BASEPATH">';</script>
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<script>
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document.addEventListener("DOMContentLoaded", (event) => {
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clusters.forEach((cluster, index) => {
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var div = document.createElement("div");
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div.textContent = "Cluster " + (index + 1);
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document.body.appendChild(div);
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cluster.forEach((id) => {
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var div = document.createElement("div");
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div.classList.add("face");
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div.style.backgroundImage = "url(face-data/" + (id % 100) + "/" + id + "-original.png)";
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document.body.appendChild(div);
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});
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});
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});
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</script>
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<style>
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body {
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margin: 0;
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padding: 0;
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}
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.face {
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width: 128px;
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height: 128px;
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background-size: contain;
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background-position: center center;
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display: inline-block;
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border: 1px solid black;
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margin: 0.5em;
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}
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</style>
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@ -6,4 +6,7 @@ ifeq ("$(wildcard /usr/include/sqlite3.h)","")
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endif
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scanner: scanner.c
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gcc -o scanner scanner.c -lm -lsqlite3
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gcc -o scanner -g scanner.c -lm -lsqlite3
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clean:
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rm scanner
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@ -6,35 +6,45 @@
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#include <math.h>
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#include <sqlite3.h>
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typedef enum {
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UNDEFINED = 0,
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CORE = 1,
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EDGE = 2,
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NOISE = 3
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} ClusterTypes;
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typedef struct Face {
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long faceId;
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long double descriptor[128];
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int faceId;
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long int clusterId;
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ClusterTypes clusterType;
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long double *distances;
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struct Face *next;
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struct Face *prev;
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} Face;
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typedef struct FaceLink {
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struct FaceLink *pNext;
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Face *pFace;
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} FaceLink;
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char fileBuf[5000];
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char pathBuf[1028];
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Face *readFaceDescriptor(int id, char *path) {
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Face *readFaceDescriptor(Face *pFace, long id, char *path) {
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FILE *f;
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Face *pFace = (Face *)malloc(sizeof(Face));
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memset(pFace, 0, sizeof(Face));
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f = fopen(path, "r");
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if (!f) {
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free(pFace);
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return NULL;
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}
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size_t s = fread(fileBuf, 1, sizeof(fileBuf), f);
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fclose(f);
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char *p = fileBuf;
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fileBuf[s] = 0;
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while (*p && *p != '-' && *p != '+' && (*p < '0' || *p > '9')) {
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p++;
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}
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for (int i = 0; i < 128; i++) {
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int i = 0;
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for (i = 0; i < 128; i++) {
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char *start = p;
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while (*p && *p != ',' && *p != ']' && *p != ' ' && *p != '\n') {
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p++;
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@ -46,14 +56,17 @@ Face *readFaceDescriptor(int id, char *path) {
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sscanf(start, "%Lf", &pFace->descriptor[i]);
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}
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if (i != 128) {
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return NULL;
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}
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pFace->faceId = id;
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pFace->next = pFace->prev = NULL;
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return pFace;
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}
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long double euclideanDistance(long double *a, long double *b) {
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long double sum = 0.0;
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long double sum = 0.0L;
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for (int i = 0; i < 128; i++) {
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long double delta = a[i] - b[i];
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sum += delta * delta;
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@ -61,16 +74,193 @@ long double euclideanDistance(long double *a, long double *b) {
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return sqrtl(sum);
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}
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int main(int argc, char *argv[]) {
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int maxId = 0;
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int len = 0;
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int i;
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Face *pChain = NULL;
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for (i = 0; i < 100; i++) {
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sprintf(pathBuf, "%s/face-data/%d", argv[1], i);
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DIR *faceDir = opendir(pathBuf);
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fprintf(stderr, "Reading %s...\n", pathBuf);
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/* https://en.wikipedia.org/wiki/DBSCAN */
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#if 0
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DBSCAN(DB, distFunc, eps, minPts) {
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C = 0 /* Cluster counter */
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for each point P in database DB {
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if label(P) ≠ undefined then continue /* Previously processed in inner loop */
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Neighbors N = RangeQuery(DB, distFunc, P, eps) /* Find neighbors */
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if |N| < minPts then { /* Density check */
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label(P) = Noise /* Label as Noise */
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continue
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}
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C = C + 1 /* next cluster label */
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label(P) = C /* Label initial point */
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Seed set S = N \ {P} /* Neighbors to expand */
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for each point Q in S { /* Process every seed point */
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if label(Q) = Noise then label(Q) = C /* Change Noise to border point */
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if label(Q) ≠ undefined then continue /* Previously processed */
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label(Q) = C /* Label neighbor */
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Neighbors N = RangeQuery(DB, distFunc, Q, eps) /* Find neighbors */
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if |N| ≥ minPts then { /* Density check */
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S = S ∪ N /* Add new neighbors to seed set */
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}
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}
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}
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}
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RangeQuery(DB, distFunc, Q, eps) {
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Neighbors = empty list
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for each point P in database DB { /* Scan all points in the database */
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if distFunc(Q, P) ≤ eps then { /* Compute distance and check epsilon */
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Neighbors = Neighbors ∪ {P} /* Add to result */
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}
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}
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return Neighbors
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}
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#endif
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FaceLink *RangeQuery(Face *pFaces, long int faceCount, Face *pQ, double eps) {
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FaceLink *pNeighbors = NULL;
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for (long int i = 0; i < faceCount; i++) {
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Face *pFace = &pFaces[i];
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if (pFace->faceId == pQ->faceId) {
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continue;
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}
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if (pQ->distances[i] <= eps) {
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FaceLink *pLink = malloc(sizeof(*pLink));
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memset(pLink, 0, sizeof(*pLink));
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pLink->pFace = pFace;
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pLink->pNext = pNeighbors;
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pNeighbors = pLink;
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}
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}
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return pNeighbors;
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}
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void freeChain(FaceLink *pLink) {
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while (pLink) {
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FaceLink *tmp = pLink->pNext;
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free(pLink);
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pLink = tmp;
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}
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}
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long int chainLength(FaceLink *pLink) {
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long int count = 0;
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while (pLink) {
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count++;
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pLink = pLink->pNext;
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}
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return count;
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}
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long int DBSCAN(Face *faces, long int faceCount, double eps, int minPts) {
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long int C = 0;
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for (long int i = 0; i < faceCount; i++) {
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Face *pFace = &faces[i];
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if (pFace->clusterType != UNDEFINED) {
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continue;
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}
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FaceLink *pNeighbors = RangeQuery(faces, faceCount, pFace, eps);
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long neighborCount = chainLength(pNeighbors);
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if (neighborCount < minPts) {
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pFace->clusterType = NOISE;
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freeChain(pNeighbors);
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continue;
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}
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//printf("%ld has %ld neighbors.\n", pFace->faceId, neighborCount);
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C++;
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pFace->clusterId = C;
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pFace->clusterType = CORE;
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FaceLink *pLink = pNeighbors;
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while (pLink) {
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Face *pQ = pLink->pFace;
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if (pQ->faceId == pFace->faceId) {
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pLink = pLink->pNext;
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continue;
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}
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if (pQ->clusterType == NOISE) {
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pQ->clusterId = C;
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pQ->clusterType = EDGE;
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}
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if (pQ->clusterType != UNDEFINED) {
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pLink = pLink->pNext;
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continue;
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}
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pQ->clusterId = C;
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pQ->clusterType = EDGE;
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FaceLink *pSubNeighbors = RangeQuery(faces, faceCount, pQ, eps);
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neighborCount = chainLength(pSubNeighbors);
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if (neighborCount >= minPts) {
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pQ->clusterType = CORE;
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/* Append these neighbors to the end of the chain */
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FaceLink *pTmp = pLink;
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while (pTmp->pNext) {
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pTmp = pTmp->pNext;
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}
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pTmp->pNext = pSubNeighbors;
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} else {
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freeChain(pSubNeighbors);
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}
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pLink = pLink->pNext;
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}
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freeChain(pNeighbors);
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}
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return C;
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}
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/*
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* 1. Count how many entries there are
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* 2. Allocate storage to hold all entries
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* 3. Read all entries into flat array
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* 4. Allocate MxM matrix and pre-calculate distances
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* 5. Perform DBSCAN across MxM matrix to cluster
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*/
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int main(int argc, char *argv[]) {
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long maxId = 0;
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long i;
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long entries = 0;
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for (i = 0; i < 100; i++) {
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sprintf(pathBuf, "%s/face-data/%ld", argv[1], i);
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DIR *faceDir = opendir(pathBuf);
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if (!faceDir) {
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continue;
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}
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struct dirent *ent;
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while ((ent = readdir(faceDir)) != NULL) {
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if (strstr(ent->d_name, ".json") == NULL) {
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continue;
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}
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entries++;
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}
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closedir(faceDir);
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}
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Face *pFaces = malloc(sizeof(Face) * entries);
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if (!pFaces) {
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fprintf(stderr, "Unable to allocate storage face descriptors.");
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return -1;
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}
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memset(pFaces, 0, sizeof(Face) * entries);
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for (i = 0; i < entries; i++) {
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pFaces[i].distances = malloc(sizeof(*pFaces[i].distances) * entries);
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if (!pFaces[i].distances) {
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fprintf(stderr, "Unable to allocate storage for distance dictionary.");
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return -1;
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}
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memset(pFaces[i].distances, 0, sizeof(*pFaces[i].distances) * entries);
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}
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entries = 0;
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for (i = 0; i < 100; i++) {
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sprintf(pathBuf, "%s/face-data/%ld", argv[1], i);
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DIR *faceDir = opendir(pathBuf);
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// fprintf(stderr, "Reading %s...\n", pathBuf);
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if (!faceDir) {
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fprintf(stderr, "Can not open %s\n", pathBuf);
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continue;
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@ -81,7 +271,7 @@ int main(int argc, char *argv[]) {
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if (strstr(ent->d_name, ".json") == NULL) {
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continue;
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}
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int id = 0;
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long id = 0;
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char *p = ent->d_name;
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while (*p && *p != '-') {
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id *= 10;
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@ -91,31 +281,92 @@ int main(int argc, char *argv[]) {
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char path[1028*2];
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sprintf(path, "%s/%s", pathBuf, ent->d_name);
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maxId = maxId > id ? maxId : id;
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Face *pFace = readFaceDescriptor(id, path);
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if (!pFace) {
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if (!readFaceDescriptor(&pFaces[entries], id, path)) {
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fprintf(stderr, "Unable to read %s.\n", path);
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continue;
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}
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len++;
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if (len % 1000 == 0) {
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fprintf(stderr, "...read %d...\n", len);
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entries++;
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if (entries % 1000 == 0) {
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fprintf(stderr, "...read %ld...\n", entries);
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}
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if (pChain) {
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pFace->next = pChain;
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}
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pChain = pFace;
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}
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closedir(faceDir);
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}
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fprintf(stderr, "Read %d face descriptors...\n", len);
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fprintf(stderr, "Read %ld face descriptors...\n", entries);
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/* Allocate storage for all distances */
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Face *pLink = pChain;
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while (pLink) {
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pLink->distances = (long double *)malloc(sizeof(long double) * len);
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pLink = pLink->next;
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long double total = 0.0;
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for (long i = 0; i < entries; i++) {
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Face *pLink = &pFaces[i];
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for (long j = 0; j < entries; j++) {
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Face *pTarget = &pFaces[j];
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if (i == j) {
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pLink->distances[i] = 0.0L;
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pTarget->distances[j] = 0.0L;
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continue;
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}
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if (pLink->distances[j] != 0.0L) {
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continue;
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}
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pLink->distances[j] =
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pTarget->distances[i] = euclideanDistance(pLink->descriptor, pTarget->descriptor);
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total += pLink->distances[j];
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}
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}
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fprintf(stderr, "Average distance: %Lf\n", (long double)1. * total / (entries * entries));
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long int clusters = DBSCAN(pFaces, entries, 0.44L, 2);
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long int undefined = 0, outlier = 0, core = 0, reachable = 0;
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for (i = 0; i < entries; i++) {
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switch (pFaces[i].clusterType) {
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case NOISE:
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outlier++;
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break;
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case UNDEFINED:
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undefined++;
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break;
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case CORE:
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core++;
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break;
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case EDGE:
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reachable++;
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break;
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}
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}
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fprintf(stderr, "%ld clusters identified!\n", clusters);
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fprintf(stderr, "%ld NOISE\n", outlier);
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fprintf(stderr, "%ld UNDEFINED\n", undefined);
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fprintf(stderr, "%ld CORE\n", core);
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fprintf(stderr, "%ld EDGE\n", reachable);
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fprintf(stdout, "<script>\nvar clusters = [\n");
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for (long i = 1; i <= clusters; i++) {
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long nodes = 0;
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fprintf(stdout, "/* %ld. */ [", i);
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for (long int j = 0; j < entries; j++) {
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if (pFaces[j].clusterId == i) {
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if (nodes == 0) {
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fprintf(stdout, "%ld", pFaces[j].faceId);
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} else {
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fprintf(stdout, ",%ld", pFaces[j].faceId);
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}
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nodes++;
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}
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}
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if (i < clusters) {
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fprintf(stdout, "],\n");
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} else {
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fprintf(stdout, "]\n");
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}
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}
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fprintf(stdout, "];\n</script>\n");
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/* Allocate storage for all distances */
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sqlite3 *db;
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int rc = sqlite3_open("db/photos.db", &db);
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@ -143,46 +394,47 @@ int main(int argc, char *argv[]) {
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fprintf(stderr, "facedistances deleted and transaction started.\n");
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char sqlBuf[1024];
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pLink = pChain;
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int sourceIndex = 0, lines = 0;
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while (pLink) {
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for (long i = 0; i < entries; i++) {
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Face *pLink = &pFaces[i];
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int targetIndex = 0;
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Face *pTarget = pChain;
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while (pTarget) {
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if (targetIndex == sourceIndex) {
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pLink->distances[targetIndex] = 0.0;
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pTarget->distances[sourceIndex] = 0.0;
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} else {
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if (pLink->distances[targetIndex] == 0.0) {
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pLink->distances[targetIndex] =
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pTarget->distances[sourceIndex] = euclideanDistance(pLink->descriptor, pTarget->descriptor);
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if (pLink->distances[targetIndex] < 0.5) {
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sprintf(sqlBuf, "INSERT INTO facedistances (face1Id,face2Id,distance) VALUES (%d,%d,%Lf);",
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((pLink->faceId < pTarget->faceId) ? pLink->faceId : pTarget->faceId),
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((pLink->faceId < pTarget->faceId) ? pTarget->faceId : pLink->faceId),
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pLink->distances[targetIndex]);
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rc = sqlite3_exec(db, sqlBuf, 0, 0, &err_msg);
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if (rc != SQLITE_OK ) {
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fprintf(stderr, "SQL error: %s\n", err_msg);
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sqlite3_free(err_msg);
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sqlite3_close(db);
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return 1;
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}
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lines++;
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if (lines % 1000 == 0) {
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fprintf(stderr, "...output %d DB lines (%0.2f complete)...\n", lines, (float)(1. * sourceIndex / (1. * len)));
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}
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}
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for (long j = 0; j < entries; j++) {
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Face *pTarget = &pFaces[j];
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if (i == j) {
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pLink->distances[i] = 0.0L;
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pTarget->distances[j] = 0.0L;
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continue;
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}
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|
||||
if (pLink->distances[j] != 0.0L) {
|
||||
// continue;
|
||||
}
|
||||
|
||||
pLink->distances[j] =
|
||||
pTarget->distances[i] = euclideanDistance(pLink->descriptor, pTarget->descriptor);
|
||||
|
||||
if (pLink->distances[j] < 0.5) {
|
||||
sprintf(sqlBuf, "INSERT INTO facedistances (face1Id,face2Id,distance) VALUES (%ld,%ld,%Lf);",
|
||||
((pLink->faceId < pTarget->faceId) ? pLink->faceId : pTarget->faceId),
|
||||
((pLink->faceId < pTarget->faceId) ? pTarget->faceId : pLink->faceId),
|
||||
pLink->distances[j]);
|
||||
rc = sqlite3_exec(db, sqlBuf, 0, 0, &err_msg);
|
||||
if (rc != SQLITE_OK ) {
|
||||
fprintf(stderr, "SQL error: %s\n", err_msg);
|
||||
sqlite3_free(err_msg);
|
||||
sqlite3_close(db);
|
||||
return 1;
|
||||
}
|
||||
lines++;
|
||||
if (lines % 1000 == 0) {
|
||||
fprintf(stderr, "...output %d DB lines (%0.2f complete)...\n", lines,
|
||||
(float)(1. * sourceIndex / (1. * entries)));
|
||||
}
|
||||
}
|
||||
pTarget = pTarget->next;
|
||||
targetIndex++;
|
||||
}
|
||||
pLink = pLink->next;
|
||||
sourceIndex++;
|
||||
}
|
||||
|
||||
sprintf(sqlBuf, "UPDATE faces SET lastComparedId=%d;", maxId);
|
||||
sprintf(sqlBuf, "UPDATE faces SET lastComparedId=%ld;", maxId);
|
||||
|
||||
rc = sqlite3_exec(db, "COMMIT;", 0, 0, &err_msg);
|
||||
if (rc != SQLITE_OK ) {
|
||||
|
||||
@ -55,7 +55,7 @@ function alignFromLandmarks(image, landmarks) {
|
||||
ctx.rotate(rotation);
|
||||
ctx.scale(scale, scale);
|
||||
ctx.drawImage(image, 0, 0);
|
||||
/*
|
||||
|
||||
ctx.strokeStyle = "red";
|
||||
ctx.strokeWidth = "1";
|
||||
ctx.beginPath();
|
||||
@ -67,7 +67,7 @@ function alignFromLandmarks(image, landmarks) {
|
||||
}
|
||||
});
|
||||
ctx.stroke();
|
||||
*/
|
||||
|
||||
return canvas;
|
||||
}
|
||||
|
||||
@ -140,20 +140,6 @@ require("./db/photos").then(function(db) {
|
||||
|
||||
const file = photo.path + photo.filename;
|
||||
return canvas.loadImage(picturesPath + file).then(async (image) => {
|
||||
const detectors = await faceapi.detectAllFaces(image,
|
||||
new faceapi.SsdMobilenetv1Options({
|
||||
minConfidence: 0.8
|
||||
})
|
||||
).withFaceLandmarks();
|
||||
|
||||
detectors.forEach(async (detector) => {
|
||||
const canvas = alignFromLandmarks(image, detector.landmarks);
|
||||
const descriptor = await faceapi.computeFaceDescriptor(canvas);
|
||||
const data = [];
|
||||
/* Confert from sparse object to dense array */
|
||||
for (let i = 0; i < 128; i++) {
|
||||
data.push(descriptor[i]);
|
||||
}
|
||||
const detectors = [ {
|
||||
detection: {
|
||||
_box: {
|
||||
@ -172,7 +158,6 @@ require("./db/photos").then(function(db) {
|
||||
/* This is a file */
|
||||
console.log(`Loading ${file}...`);
|
||||
id = undefined;
|
||||
|
||||
loader = canvas.loadImage(picturesPath + file).then(async (image) => {
|
||||
const detectors = await faceapi.detectAllFaces(image,
|
||||
new faceapi.SsdMobilenetv1Options({
|
||||
@ -183,10 +168,19 @@ require("./db/photos").then(function(db) {
|
||||
detectors.forEach(async (detector) => {
|
||||
const canvas = alignFromLandmarks(image, detector.landmarks);
|
||||
const descriptor = await faceapi.computeFaceDescriptor(canvas);
|
||||
|
||||
fs.writeFileSync("rotation.png", canvas.toBuffer("image/png", {
|
||||
quality: 0.95,
|
||||
chromaSubsampling: false
|
||||
}));
|
||||
|
||||
process.exit(-1);
|
||||
|
||||
// .withFaceDescriptors();
|
||||
const data = [];
|
||||
/* Confert from sparse object to dense array */
|
||||
for (let i = 0; i < 128; i++) {
|
||||
data.push(descriptor[i]);
|
||||
data.push(detector.descriptor[i]);
|
||||
}
|
||||
detector.descriptor = data;
|
||||
});
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user