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21      tech: ["Python", "TensorFlow", "React"],
22      link: "https://ai-chatbot.example.com",
23      image: "https://maxm-imggenurl.web.val.run/ai-chatbot-interface",
24    },
25    {
28      tech: ["Solidity", "Web3.js", "React"],
29      link: "https://blockchain-explorer.example.com",
30      image: "https://maxm-imggenurl.web.val.run/blockchain-dashboard",
31    },
32    {
35      tech: ["Node.js", "MQTT", "React Native"],
36      link: "https://smart-home.example.com",
37      image: "https://maxm-imggenurl.web.val.run/smart-home-dashboard",
38    },
39  ];
211              >
212                <img
213                  src={project.image}
214                  alt={project.title}
215                  className="w-full h-48 object-cover rounded-t-lg mb-4"

7function App() {
8  const [prompt, setPrompt] = useState("");
9  const [imageUrl, setImageUrl] = useState("");
10  const [loading, setLoading] = useState(false);
11
12  const generateImage = async (e?: React.FormEvent) => {
13    e?.preventDefault();
14    setLoading(true);
21        input: {
22          prompt,
23          image_size: "landscape_4_3",
24          num_inference_steps: 4,
25          num_images: 1,
26          enable_safety_checker: true,
27          sync_mode: true,
28        },
29      });
30      setImageUrl(result.data.images[0].url);
31    } catch (error) {
32      console.error("Error generating image:", error);
33    } finally {
34      setLoading(false);
39    <div className="min-h-screen bg-black text-white py-12 px-4 sm:px-6 lg:px-8">
40      <div className="max-w-3xl mx-auto">
41        <h1 className="text-4xl font-bold text-center mb-8">Fal AI Image Generator</h1>
42        <div className="bg-gray-900 rounded-lg p-6 mb-8 shadow-lg">
43          <form className="flex flex-col sm:flex-row gap-4" onSubmit={generateImage}>
44            <input
45              type="text"
46              value={prompt}
47              onChange={(e) => setPrompt(e.target.value)}
48              placeholder="Enter your image prompt"
49              className="flex-grow px-4 py-2 bg-gray-800 border border-gray-700 rounded-md focus:ring-2 focus:ring-blue-500 focus:border-transparent"
50            />
51            <button
52              onClick={generateImage}
53              disabled={loading || !prompt}
54              className={`px-6 py-2 rounded-md text-white font-medium transition-colors duration-200 ${
80                )
81                : (
82                  "Generate Image"
83                )}
84            </button>
85          </form>
86        </div>
87        {imageUrl && (
88          <div className="bg-gray-900 rounded-lg overflow-hidden shadow-lg">
89            <img src={imageUrl} alt="Generated image" className="w-full h-auto" />
90          </div>
91        )}
118          <meta charset="UTF-8">
119          <meta name="viewport" content="width=device-width, initial-scale=1.0">
120          <title>Fal AI Image Generator</title>
121          <script src="https://cdn.tailwindcss.com"></script>
122          <style>

4
5<div align="center">
6<img src="https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/67a1d35e-c37c-41a4-0e5a-03a9ba585d00/public" width="700px"/>
7</div>

9## Example
10This val tracks mentions of "Val Town" and related terms, excluding noise like retweets and irrelevant accounts. Notifications are sent to a Discord webhook but can be easily reconfigured for other platforms.
11<img src="https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/85912106-f625-443e-5321-6e2699453200/public" width="500"/>
12To see exactly how we use this template at Val Town: https://www.val.town/v/stevekrouse/twitterAlert
13
16### 1. Fork this Val
17To use this template, fork this val on the top right corner of this page.
18![Screenshot 2025-01-10 at 1.22.10 PM.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/c4ae349d-7e28-4378-8646-21c8958e1f00/public)
19
20### 2. View Source Code
21<em>The `CODE` box shows you the the full source code of this val, you may need to scroll down to see it.</em>
22![image.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/6a4dabb4-3b27-4cea-fce3-95a1a1c3cd00/public)
23
24### 3. Customize Query

1# ☔️ Umbrella reminder if there's rain today
2
3![Screenshot 2023-09-14 at 12.31.32.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/d82916ca-f8d9-4b49-88c6-420ab67a7700/public)
4
5## Setup

1165        <meta property="og:description" content="Turn your ideas into fully functional apps in less than a second – powered by Llama3.3-70b on Cerebras's super-fast wafer chips. Code is 100% open-source, hosted on Val Town."">
1166        <meta property="og:type" content="website">
1167        <meta property="og:image" content="https://stevekrouse-blob_admin.web.val.run/api/public/CerebrasCoderOG.jpg">
1168        
1169            

1165        <meta property="og:description" content="Turn your ideas into fully functional apps in less than a second – powered by Llama3.3-70b on Cerebras's super-fast wafer chips. Code is 100% open-source, hosted on Val Town."">
1166        <meta property="og:type" content="website">
1167        <meta property="og:image" content="https://stevekrouse-blob_admin.web.val.run/api/public/CerebrasCoderOG.jpg">
1168        
1169            

1"Identify and extract text from the uploaded image accurately, ensuring multi-language support. Clean unnecessary noise or artifacts, and format the text for readability. Highlight important headings or bold text if detected in the image."
2
3डिटेल्ड प्रॉम्प्ट:
4"Analyze the uploaded image and detect text using OCR. The model should:
5
61. Recognize all text areas, even if they are handwritten or in different fonts.
10
11
123. Remove image artifacts like shadows or noise.
13
14

1import pytesseract
2from pytesseract import Output
3from PIL import Image
4import cv2
5import os
9
10# इमेज प्रोसेसिंग के लिए फंक्शन
11def process_image(image_path, output_format="txt"):
12    try:
13        # इमेज को लोड करें और प्रोसेस करें
14        image = cv2.imread(image_path)
15        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
16
17        # नॉइज़ रिमूवल
18        processed_image = cv2.GaussianBlur(gray, (5, 5), 0)
19
20        # OCR से टेक्स्ट पहचान
21        text_data = pytesseract.image_to_string(processed_image, lang="eng+hin+ben", config='--psm 6')
22
23        # टेक्स्ट फॉर्मेट करना
31        
32        elif output_format == "pdf":
33            pdf_output = pytesseract.image_to_pdf_or_hocr(processed_image, extension='pdf')
34            with open("output_document.pdf", "wb") as file:
35                file.write(pdf_output)
40
41# इमेज का पथ
42image_path = "sample_image.jpg"  # अपनी इमेज का पथ दें
43output_format = "pdf"  # 'txt' या 'pdf' में से चुनें
44
45# फंक्शन को कॉल करें
46process_image(image_path, output_format)

68  let content = "New user! " + emailAddress
69    + " "
70    + data.profile_image_url;
71
72  if (emailInfo.services.length || emailInfo.social_media.length) {