add modelname to the image file

Package.swift

@@ -31,13 +31,5 @@ let package = Package(
                 "StableDiffusion",
                 .product(name: "ArgumentParser", package: "swift-argument-parser")],
             path: "swift/StableDiffusionCLI"),
-        .testTarget(
-            name: "StableDiffusionTests",
-            dependencies: ["StableDiffusion"],
-            path: "swift/StableDiffusionTests",
-            resources: [
-                .copy("Resources/vocab.json"),
-                .copy("Resources/merges.txt")
-            ]),
     ]
 )

python_coreml_stable_diffusion/pipeline.py

@@ -267,7 +267,7 @@ class CoreMLStableDiffusionPipeline(DiffusionPipeline):
         prompt,
         height=512,
         width=512,
-        num_inference_steps=50,
+        num_inference_steps=100,
         guidance_scale=7.5,
         negative_prompt=None,
         num_images_per_prompt=1,
@@ -528,7 +528,7 @@ if __name__ == "__main__":
              "If not specified, the default scheduler from the diffusers pipeline is utilized"))
     parser.add_argument(
         "--num-inference-steps",
-        default=50,
+        default=75,
         type=int,
         help="The number of iterations the unet model will be executed throughout the reverse diffusion process")
     parser.add_argument(

python_coreml_stable_diffusion/torch2coreml.py

@@ -839,7 +839,8 @@ def parser_spec():
     parser.add_argument("--convert-safety-checker", action="store_true")
     parser.add_argument(
         "--model-version",
-        default="CompVis/stable-diffusion-v1-4",
+        #default="CompVis/stable-diffusion-v1-4",
+        default="prompthero/openjourney-v2",
         help=
         ("The pre-trained model checkpoint and configuration to restore. "
          "For available versions: https://huggingface.co/models?search=stable-diffusion"

runsd.js

@@ -0,0 +1,34 @@
+#!/usr/bin/env node
+
+const fs = require('fs');
+const util = require('util');
+const exec = util.promisify(require('child_process').exec);
+const readFile = util.promisify(fs.readFile);
+
+async function run() {
+    const models = ['runwaymlsd15/Resources', 'openjourneyv2/Resources', 'compiled'];
+    let prompts = (await readFile('prompts.txt', 'utf8')).split('\n');
+    let index = 0;
+
+    while (index < prompts.length) {
+        for (const model of models) {
+            const prompt = prompts[index];
+            console.log(`Running ${model} on prompt: ${prompt}...`);
+            // run the specific command for the model on the prompt
+            const { stdout, stderr } = await exec(`./StableDiffusionSample --resource-path ${model} "${prompt}" --step-count 120`);
+            console.log(stdout);
+            console.error(stderr);
+            console.log('Done.');
+            console.log();
+
+            // check if any new prompts have been added to the file
+            const updatedPrompts = (await readFile('prompts.txt', 'utf8')).split('\n');
+            if (updatedPrompts.length > prompts.length) {
+                prompts = updatedPrompts;
+            }
+        }
+        index++;
+    }
+}
+
+run().catch(error => console.error(error));

swift/StableDiffusionCLI/main.swift

@@ -8,6 +8,7 @@ import Foundation
 import StableDiffusion
 import UniformTypeIdentifiers
 
+
 @available(iOS 16.2, macOS 13.1, *)
 struct StableDiffusionSample: ParsableCommand {
 
@@ -31,13 +32,13 @@ struct StableDiffusionSample: ParsableCommand {
             valueName: "directory-path"
         )
     )
-    var resourcePath: String = "./"
+    var resourcePath: String = "compiled"
 
     @Option(help: "Number of images to sample / generate")
-    var imageCount: Int = 1
+    var imageCount: Int = 4
 
     @Option(help: "Number of diffusion steps to perform")
-    var stepCount: Int = 50
+    var stepCount: Int = 100
 
     @Option(
         help: ArgumentHelp(
@@ -50,8 +51,12 @@ struct StableDiffusionSample: ParsableCommand {
     @Option(help: "Output path")
     var outputPath: String = "./"
 
+
+    
     @Option(help: "Random seed")
-    var seed: UInt32 = 93
+    var seed: UInt32 = UInt32(arc4random())
+    
+    
 
     @Option(help: "Controls the influence of the text prompt on sampling process (0=random images)")
     var guidanceScale: Float = 7.5
@@ -63,7 +68,7 @@ struct StableDiffusionSample: ParsableCommand {
     var scheduler: SchedulerOption = .pndm
 
     @Flag(help: "Disable safety checking")
-    var disableSafety: Bool = false
+    var disableSafety: Bool = true
 
     @Flag(help: "Reduce memory usage")
     var reduceMemory: Bool = false
@@ -165,6 +170,7 @@ struct StableDiffusionSample: ParsableCommand {
     func imageName(_ sample: Int, step: Int? = nil) -> String {
         let fileCharLimit = 75
         var name = prompt.prefix(fileCharLimit).replacingOccurrences(of: " ", with: "_")
+        var modelName = resourcePath.replacingOccurrences(of: "/", with: "_")
         if imageCount != 1 {
             name += ".\(sample)"
         }
@@ -174,7 +180,7 @@ struct StableDiffusionSample: ParsableCommand {
         if let step = step {
             name += ".\(step)"
         } else {
-            name += ".final"
+            name += ".\(modelName)"
         }
         name += ".png"
         return name

swift/StableDiffusionTests/StableDiffusionTests.swift

@@ -1,63 +0,0 @@
-// For licensing see accompanying LICENSE.md file.
-// Copyright (C) 2022 Apple Inc. All Rights Reserved.
-
-import XCTest
-import CoreML
-@testable import StableDiffusion
-
-@available(iOS 16.2, macOS 13.1, *)
-final class StableDiffusionTests: XCTestCase {
-
-    var vocabFileInBundleURL: URL {
-        let fileName = "vocab"
-        guard let url = Bundle.module.url(forResource: fileName, withExtension: "json") else {
-            fatalError("BPE tokenizer vocabulary file is missing from bundle")
-        }
-        return url
-    }
-
-    var mergesFileInBundleURL: URL {
-        let fileName = "merges"
-        guard let url = Bundle.module.url(forResource: fileName, withExtension: "txt") else {
-            fatalError("BPE tokenizer merges file is missing from bundle")
-        }
-        return url
-    }
-
-    func testBPETokenizer() throws {
-
-        let tokenizer = try BPETokenizer(mergesAt: mergesFileInBundleURL, vocabularyAt: vocabFileInBundleURL)
-
-        func testPrompt(prompt: String, expectedIds: [Int]) {
-
-            let (tokens, ids) = tokenizer.tokenize(input: prompt)
-
-            print("Tokens          = \(tokens)\n")
-            print("Expected tokens = \(expectedIds.map({ tokenizer.token(id: $0) }))")
-            print("ids             = \(ids)\n")
-            print("Expected Ids    = \(expectedIds)\n")
-
-            XCTAssertEqual(ids,expectedIds)
-        }
-
-        testPrompt(prompt: "a photo of an astronaut riding a horse on mars",
-                   expectedIds: [49406, 320, 1125, 539, 550, 18376, 6765, 320, 4558, 525, 7496, 49407])
-
-        testPrompt(prompt: "Apple CoreML developer tools on a Macbook Air are fast",
-                   expectedIds: [49406,  3055, 19622,  5780, 10929,  5771,   525,   320, 20617,
-                                 1922,   631,  1953, 49407])
-    }
-
-    func test_randomNormalValues_matchNumPyRandom() {
-        var random = NumPyRandomSource(seed: 12345)
-        let samples = random.normalArray(count: 10_000)
-        let last5 = samples.suffix(5)
-
-        // numpy.random.seed(12345); print(numpy.random.randn(10000)[-5:])
-        let expected = [-0.86285345, 2.15229409, -0.00670556, -1.21472309, 0.65498866]
-
-        for (value, expected) in zip(last5, expected) {
-            XCTAssertEqual(value, expected, accuracy: .ulpOfOne.squareRoot())
-        }
-    }
-}