Update app.py

app.py

@@ -1,46 +1,28 @@
-import streamlit as st
-import PyPDF2
-import docx
-import spacy
-
-# Load NLP model
-@st.cache_resource
-def load_model():
-    return spacy.load("en_core_web_sm")
-
-nlp = load_model()
-
-# Function to extract text
-def extract_text(file):
-    if file.type == "application/pdf":
-        reader = PyPDF2.PdfFileReader(file)
-        return "".join([reader.getPage(i).extract_text() for i in range(reader.numPages)])
-    elif file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-        return "\n".join([para.text for para in docx.Document(file).paragraphs])
-
-# Function to extract and display information
-def analyze_resume(text, job_desc):
-    doc = nlp(text)
-    extracted_info = {"skills": [], "education": [], "experience": []}
-    
-    for ent in doc.ents:
-        if ent.label_ in ["ORG", "GPE"]:
-            extracted_info["education"].append(ent.text)
-        elif ent.label_ == "DATE":
-            extracted_info["experience"].append(ent.text)
-
-    match_score = sum(1 for token in nlp(job_desc) if token.text in text) / len(job_desc.split()) * 100
-    return extracted_info, match_score
-
-# Streamlit interface
-st.title("Resume Scanner with NLP")
-uploaded_file = st.file_uploader("Upload a resume (PDF or DOCX)", type=["pdf", "docx"])
-job_description = st.text_area("Paste the job description here")
-
-if uploaded_file and job_description:
-    resume_text = extract_text(uploaded_file)
-    extracted_info, match_score = analyze_resume(resume_text, job_description)
-    
-    st.subheader("Extracted Information:")
-    st.write(extracted_info)
-    st.subheader(f"Match Score: {match_score:.2f}%")
+import streamlit as st
+import easyocr
+from PIL import Image
+
+# Initialize the EasyOCR Reader
+reader = easyocr.Reader(['en'])
+
+# Streamlit interface
+st.title("OCR with EasyOCR")
+
+# Upload image
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file:
+    # Open image file
+    image = Image.open(uploaded_file)
+    st.image(image, caption='Uploaded Image', use_column_width=True)
+
+    # Run OCR
+    result = reader.readtext(image)
+
+    # Display OCR results
+    st.subheader("OCR Results:")
+    for detection in result:
+        text = detection[1]
+        bbox = detection[0]
+        st.write(f"Text: {text}")
+        st.write(f"Bounding Box: {bbox}")