44

.vs/PuLID/v17/DocumentLayout.json

@@ -0,0 +1,37 @@
+{
+  "Version": 1,
+  "WorkspaceRootPath": "C:\\Users\\piotr\\Documents\\GitHub\\PuLID\\",
+  "Documents": [
+    {
+      "AbsoluteMoniker": "D:0:0:{A2FE74E1-B743-11D0-AE1A-00A0C90FFFC3}|\u003CMiscFiles\u003E|C:\\Users\\piotr\\Documents\\GitHub\\PuLID\\app.py||{8B382828-6202-11D1-8870-0000F87579D2}",
+      "RelativeMoniker": "D:0:0:{A2FE74E1-B743-11D0-AE1A-00A0C90FFFC3}|\u003CMiscFiles\u003E|solutionrelative:app.py||{8B382828-6202-11D1-8870-0000F87579D2}"
+    }
+  ],
+  "DocumentGroupContainers": [
+    {
+      "Orientation": 0,
+      "VerticalTabListWidth": 256,
+      "DocumentGroups": [
+        {
+          "DockedWidth": 200,
+          "SelectedChildIndex": 0,
+          "Children": [
+            {
+              "$type": "Document",
+              "DocumentIndex": 0,
+              "Title": "app.py",
+              "DocumentMoniker": "C:\\Users\\piotr\\Documents\\GitHub\\PuLID\\app.py",
+              "RelativeDocumentMoniker": "app.py",
+              "ToolTip": "C:\\Users\\piotr\\Documents\\GitHub\\PuLID\\app.py",
+              "RelativeToolTip": "app.py",
+              "ViewState": "AgIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA==",
+              "Icon": "00000000-0000-0000-0000-000000000000.000000|iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAHeSURBVDhPpVMxa1NRFP7ebZLSlgaltNpSVCySRUxL0NAh4FJpHWpxcZAUBEPG/AKHDsVBN5eGrCnoYKCDoDiUCKKBjtZBUZtJ2ojYJr40ue\u002B\u002B47k3VzD0hQr94OOed8853/k47z2cCETk2NAgk8mQDQMhhFjK5/Mb9vEotIDruoEsFovEzVvZbPaWLTcQ9uxCpVLp4l\u002Bk0\u002BlEPB5/wIPm7RVC9uxCMpm0UTdKpRKi0WiCQy3wUt8FCvw7VSNxbRapG4voDwucGgyjXC7bzH84ePt1HysbH/GhWoNstzA1OoSFhZuxQqFg8sfu4FutAd\u002BT8KSEYm7v7GJ0YnLClgYLaAcjU9N4Vx9Dda8OBz7OjwywSNsIXY39vEL7TxWpxv2eO3hWHUZ19xc8ti25UdvXzdpNWH0BDj8JiLOrPXfweOu9mRgRhOXUEPr7IiBfYeacB9HaBNRvQH4f6\u002BlgMERwGxJP7grEoq9shj9Uz\u002BVGpmIi4vXcwdzlcePgzLAuZPiSGw869Jg\u002Biw1Mvw50oLGcuoh71y8h1HwB1Js8UfFLnwScNnBhdYVLWsy1IwK5XM5GHaw9uu0LeSCMddZA32lz7zjOQxMcByK1SPU3O/Rjnai2fkjNz8/5L77TyQJ/AJc67LNf3QeWAAAAAElFTkSuQmCC",
+              "WhenOpened": "2024-09-25T16:57:46.945Z",
+              "EditorCaption": ""
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}

.vs/VSWorkspaceState.json

@@ -0,0 +1,7 @@
+{
+  "ExpandedNodes": [
+    ""
+  ],
+  "SelectedNode": "\\C:\\Users\\piotr\\Documents\\GitHub\\PuLID",
+  "PreviewInSolutionExplorer": false
+}

.vscode/launch.json

@@ -0,0 +1,22 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python Debugger: Current File",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal"
+        },
+        {
+            "type": "chrome",
+            "request": "launch",
+            "name": "Launch Chrome against localhost",
+            "url": "http://localhost:8080",
+            "webRoot": "${workspaceFolder}"
+        }
+    ]
+}

check_cuda.py

@@ -0,0 +1,16 @@
+import torch
+
+def get_device_properties(device: int):
+    """Zwraca właściwości urządzenia CUDA dla podanego urządzenia."""
+    return torch.cuda.get_device_properties(device)
+
+if __name__ == "__main__":
+    if torch.cuda.is_available():
+        device_count = torch.cuda.device_count()
+        for i in range(device_count):
+            properties = get_device_properties(i)
+            print(f"Urządzenie {i}: {properties.name}")
+            print(f"Całkowita pamięć: {properties.total_memory // (1024**2)} MB")
+            print(f"Liczba multiprocessorów: {properties.multi_processor_count}\n")
+    else:
+        print("CUDA nie jest dostępne.")

docs/pulid_for_flux.md

@@ -70,7 +70,7 @@ As shown in the above image, in terms of ID fidelity, using fake CFG is similar
 ## Some Technical Details
 - We switch the ID encoder from an MLP structure to a Transformer structure. Interested users can refer to [source code](https://github.com/ToTheBeginning/PuLID/blob/cce7cdd65b5bf283c1a39c29f2726902a3c135ca/pulid/encoders_flux.py#L122)
 - Inspired by [Flamingo](https://arxiv.org/abs/2204.14198), we insert additional cross-attention blocks every few DIT blocks to interact ID features with DIT image features
-- We would like to clarify that the acceleration method (lile SDXL-Lightning) serves as an
+- We would like to clarify that the acceleration method (like SDXL-Lightning) serves as an
 optional acceleration trick, but it is not indispensable for training PuLID. We will update the arxiv paper with the relevant details in the near future. Please stay tuned.
 
 
@@ -81,4 +81,4 @@ The model is currently in beta version, and we have observed that the ID fidelit
 As long as you use FLUX.1-dev model, you should follow the [FLUX.1-dev model license](https://github.com/black-forest-labs/flux/tree/main/model_licenses)
 
 ## contact
-If you have any questions or suggestions about the model, please contact [Yanze Wu](https://tothebeginning.github.io/) or open an issue/discussion here.
+If you have any questions or suggestions about the model, please contact [Yanze Wu](https://tothebeginning.github.io/) or open an issue/discussion here.

myenv/Include/site/python3.12/insightface/mesh_core.h

@@ -0,0 +1,83 @@
+#ifndef MESH_CORE_HPP_
+#define MESH_CORE_HPP_
+
+#include <stdio.h>
+#include <cmath>
+#include <algorithm>  
+#include <string>
+#include <iostream>
+#include <fstream>
+
+using namespace std;
+
+class point
+{
+ public:
+    float x;
+    float y;
+
+    float dot(point p)
+    {
+        return this->x * p.x + this->y * p.y;
+    }
+
+    point operator-(const point& p)
+    {
+        point np;
+        np.x = this->x - p.x;
+        np.y = this->y - p.y;
+        return np;
+    }
+
+    point operator+(const point& p)
+    {
+        point np;
+        np.x = this->x + p.x;
+        np.y = this->y + p.y;
+        return np;
+    }
+
+    point operator*(float s)
+    {
+        point np;
+        np.x = s * this->x;
+        np.y = s * this->y;
+        return np;
+    }
+}; 
+
+
+bool isPointInTri(point p, point p0, point p1, point p2, int h, int w);
+void get_point_weight(float* weight, point p, point p0, point p1, point p2);
+
+void _get_normal_core(
+    float* normal, float* tri_normal, int* triangles,
+    int ntri);
+
+void _rasterize_triangles_core(
+    float* vertices, int* triangles, 
+    float* depth_buffer, int* triangle_buffer, float* barycentric_weight,
+    int nver, int ntri,
+    int h, int w);
+
+void _render_colors_core(
+    float* image, float* vertices, int* triangles, 
+    float* colors, 
+    float* depth_buffer,
+    int nver, int ntri,
+    int h, int w, int c);
+
+void _render_texture_core(
+    float* image, float* vertices, int* triangles, 
+    float* texture, float* tex_coords, int* tex_triangles, 
+    float* depth_buffer,
+    int nver, int tex_nver, int ntri, 
+    int h, int w, int c, 
+    int tex_h, int tex_w, int tex_c, 
+    int mapping_type);
+
+void _write_obj_with_colors_texture(string filename, string mtl_name, 
+    float* vertices, int* triangles, float* colors, float* uv_coords,
+    int nver, int ntri, int ntexver);
+
+#endif